Training Example: Apache Hive – Review the Data, Give Your Score & Compare to the Real AI Evaluation

Industry Context — Common BS Fingerprints in Software, SaaS & Tech Products
Generic Claims: the all-in-one platform, trusted by thousands of companies, increase productivity by X percent, save hours every week…
Red Flags: AI claims without explaining what the AI does, customer logos without case study or testimonial evidence, no live product access or demo, SOC 2 claims without audit period or report availability…
Semantic Drift Patterns: homepage claims AI-powered but product is rules-based, claims enterprise-grade but pricing page shows startup tiers only, homepage shows Fortune 500 logos but case studies are small businesses, claims all-in-one but integration page shows critical missing pieces…
Proof Expectations: live product demo or free trial access, specific feature documentation with screenshots, verified customer logos with published case studies, third-party review scores on G2, Capterra, or TrustRadius…

Apache Hive

(https://hive.apache.org) 📸 Data Snapshot: May 27, 2026

Analyze the raw signals below. How would a machine score this business’s credibility?

Here are the exact signals captured from up to six pages of the site — the same raw inputs the evaluation engine analyzed. They are grouped by signal type so you can weigh each the way the machine does.

🏗️ Semantic Structure — heading hierarchy & page identity (Info Density · Commodity Fingerprint)
HOMEPAGE Apache Hive (https://hive.apache.org)
Title

Apache Hive

H1 Apache Hive
H2 Why Choose Apache Hive?
H2 What is Apache Hive?
H2 Key Features & Capabilities
H2 Ready to Get Started with Apache Hive?
H3 Used by Industry Leaders
H3 HiveServer2 (HS2)
H3 Hive Metastore Server (HMS)
H3 ACID Transactions
H3 Data Compaction
H3 Apache Iceberg Support
H3 Security & Observability
H3 Low Latency Analytics (LLAP)
H3 Cost-Based Optimizer
H3 Data Replication
H4 Battle-Tested Performance
H4 Vibrant Ecosystem
H4 SQL-First Approach
H4 Cloud-Native Ready
H4 Enterprise Security
H4 Apache Foundation
H5 Central Metadata Repository
H5 SQL Analytics at Scale
NAV_HEADER_HEADING_REPEATED_BODY Getting Started (https://hive.apache.org//development/gettingstarted/)
Title

Getting Started

H1 Getting Started
H2 Quick start with Docker
H4 Table of Contents
H4 Feedback
H4 On this page
NAV_HEADER_HEADING_REPEATED_BODY Mailing Lists (https://hive.apache.org//community/mailinglists/)
Title

Mailing Lists

H1 Mailing Lists
H2 User Mailing List
H2 Developer Mailing List
H2 Issues Mailing List
H2 Commits Mailing List
H2 Security Mailing List
H4 Table of Contents
H4 Feedback
H4 On this page
NAV_HEADER_HEADING_REPEATED Documentation (https://hive.apache.org//docs/latest/)
Title

Documentation

H1 Documentation
H2 Table of Contents
H2 Hive + Gravitino + Keycloak
H2 Release 4.0.0 – 2024-03-29
H3 Hive 4.2.0 – REST Catalog Integration
H3 Architecture Overview
H3 Administration Manual
H3 HCatalog Manual
H3 Language Manual
H3 User Manual
H3 WebHCat (Templeton) Manual
H3 Apache Hive : ChangeLog
H3 NEW FEATURES:
H3 IMPROVEMENTS:
H3 BUG FIXES:
H3 TESTS:
H3 SUB-TASKS:
H3 OTHER:
H3 Hive 4.0 – Overview of Major Changes
H3 Iceberg Integration
H3 Hive ACID
H3 Compaction
H3 Hive Metastore
H3 HiveServer2
H3 Hive Replication
H3 Security
H3 Compiler
H3 Miscl.
H3 Introduction to Apache Hive
📝 The Narrative — clean text per page (Info Density · Semantic Coherence)
HOMEPAGE (https://hive.apache.org) Apache Hive
NEW RELEASE
Apache Hive 4.2.0 is now available!
Featuring JDK 21 support, enhanced Iceberg integration with v3 capabilities (Deletion Vectors, column defaults, Z-ordering, Variant type), built-in auto-compaction, REST Catalog client support; HMS REST Catalog, and improved performance. Download
Details18+Years of Development1000+Enterprise DeploymentsPetabytesData Processed DailyGlobalCommunity
[H2] Why Choose Apache Hive?
Trusted by enterprises worldwide for mission-critical data analytics
[H3] Used by Industry Leaders
[IMG: Cloudera]
[IMG: Amazon AWS]
[IMG: Microsoft Azure]
[IMG: Google Cloud]
[IMG: Databricks]
[IMG: Treasure AI]
[H4] Battle-Tested Performance
Over 18 years of development and optimization, handling petabytes of data in production environments across the globe.
[H4] Vibrant Ecosystem
Seamlessly integrates with Spark, Presto, Impala, and hundreds of other tools in the modern data stack.
[H4] SQL-First Approach
Familiar SQL interface makes it easy for data analysts and engineers to work with big data without learning new languages.
[H4] Cloud-Native Ready
Native support for S3, Azure Data Lake, Google Cloud Storage, and other cloud storage systems.
[H4] Enterprise Security
Comprehensive security features including Kerberos authentication, fine-grained access control, and audit logging.
[H4] Apache Foundation
Backed by the Apache Software Foundation with a strong commitment to open source principles and community governance.
[H2] What is Apache Hive?
Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale.
[H5] Central Metadata Repository
Hive Metastore (HMS) provides a central repository of metadata that can easily be analyzed to make informed, data driven decisions, making it a critical component of many data lake architectures.
[H5] SQL Analytics at Scale
Built on top of Apache Hadoop with support for S3, ADLS, GS and more. Hive allows users to read, write, and manage petabytes of data using familiar SQL syntax.
[H2] Key Features & Capabilities
Powerful tools for modern data analytics and managementbeeline -u "jdbc:hive2://host:10001/default"
Connected to: Apache Hive
jdbc:hive2://host:10001/>select count(*) from test_t1;
[H3] HiveServer2 (HS2)
HS2 supports multi-client concurrency and authentication with better support for open API clients like JDBC and ODBC, enabling seamless integration with business intelligence tools and applications.Learn More
[IMG: Hive Metastore]
[H3] Hive Metastore Server (HMS)
The central repository of metadata for Hive tables and partitions, providing clients including Hive, Impala, and Spark access through the metastore service API. A fundamental building block for modern data lakes.Learn More
[IMG: Hive ACID]
[H3] ACID Transactions
Full ACID support for ORC tables and insert-only support for all other formats, ensuring data consistency and reliability in concurrent environments.Learn More jdbc:hive2://> alter table test_t1 compact "MAJOR";
Done!
jdbc:hive2://> alter table test_t1 compact "MINOR";
Done!
jdbc:hive2://> show compactions;
[H3] Data Compaction
Query-based and MapReduce-based data compactions are supported out-of-the-box, optimizing storage efficiency and query performance.Learn More
[IMG: Hive Iceberg Integration]
[H3] Apache Iceberg Support
Out-of-the-box support for Apache Iceberg tables, a cloud-native, high-performance open table format, via Hive StorageHandler for modern data lake architectures.Learn More
[IMG: Kerberos]
[IMG: Apache Atlas]
[IMG: Apache Ranger]
[H3] Security & Observability
Enterprise-grade security with Kerberos authentication and seamless integration with Apache Ranger for authorization and Apache Atlas for data lineage and governance.Learn More
[IMG: LLAP]
[H3] Low Latency Analytics (LLAP)
Interactive and sub-second SQL queries through persistent query infrastructure and optimized data caching, making Hive suitable for real-time analytics workloads.Learn More jdbc:hive2://> explain cbo select ss.ss_net_profit, sr.sr_net_loss from store_sales ss join store_returns sr on (ss.ss_item_sk=sr.sr_item_sk) limit 5 ;
+---------------------------------------------+
Explain +---------------------------------------------+
CBO PLAN: HiveSortLimit(fetch=[5]) HiveProject(ss_net_profit=[$1], sr_net_loss=[$3])   HiveJoin(condition=[=($0, $2)], joinType=[inner])     HiveProject(ss_item_sk=[$2], ss_net_profit=[$22])     HiveFilter(condition=[IS NOT NULL($2)])       HiveTableScan(table=[[tpcds_text_10, store_sales]], table:alias=[ss])     HiveProject(sr_item_sk=[$2], sr_net_loss=[$19])     HiveFilter(condition=[IS NOT NULL($2)])       HiveTableScan(table=[[tpcds_text_10, store_returns]], table:alias=[sr]) +---------------------------------------------+
[H3] Cost-Based Optimizer
Apache Calcite's cost-based query optimizer (CBO) and execution framework automatically optimize SQL queries for optimal performance and resource utilization.Learn More jdbc:hive2://> repl dump src with (
'hive.repl.dump.version'= '2',
'hive.repl.rootdir'= 'hdfs://<host>:<port>/user/replDir/d1'
);
Done!
jdbc:hive2://> repl load src into tgt with (
'hive.repl.rootdir'= 'hdfs://<host>:<port>/user/replDir/d1'
);
Done!
[H3] Data Replication
Bootstrap and incremental replication capabilities for robust backup and disaster recovery, ensuring business continuity and data protection.Learn More
[H2] Ready to Get Started with Apache Hive?
Join thousands of organizations using Apache Hive to power their data analytics and build modern data lakes. Start Your Journey
Try with Docker
Documentation
Source Code
Mailing Lists
Contribute
5675 chars
SUB-PAGE (https://hive.apache.org//development/gettingstarted/) Getting Started
[H4] Table of Contents
The Apache Hive ™ data warehouse software facilitates reading,
writing, and managing large datasets residing in distributed storage
using SQL. Structure can be projected onto data already in storage.
A command line tool and JDBC driver are provided to connect users to
Hive.
[H1] Getting Started With Apache Hive Software
Check out the Getting Started Guide.Learn more About Hive’s Functionality.Read the Getting Started Guide to learn how to install HiveThe User and Hive SQL documentation shows how to program Hive
[H2] Quick start with Docker
Checkout the quickstart with Docker here: DOCKER_QUICKSTART
[H1] Getting Involved With The Apache Hive Community
Apache Hive is an open source project run by volunteers at the Apache
Software Foundation. Previously it was a subproject of Apache®
Hadoop®, but has now graduated to become a
top-level project of its own. We encourage you to learn about the
project and contribute your expertise.Give us feedback or submit bug reports: What can we do better?Join the mailing list and meet our communityRead through our Contributor’s Guides about where to find the source or submit patchesBecome a Hive Fan on FacebookFollow @ApacheHive on Twitter
1212 chars
SUB-PAGE (https://hive.apache.org//community/mailinglists/) Mailing Lists
[H4] Table of Contents
[H1] Mailing Lists
We welcome you to join our mailing lists and let us know about your thoughts or
ideas about Hive.
[H2] User Mailing List
The user list is for general discussion or questions on using Hive. Hive
developers monitor this list and provide assistance when needed.Subscribe: user-subscribe@hive.apache.orgPost: user@hive.apache.orgUnsubscribe: user-unsubscribe@hive.apache.orgArchives: Apache
[H2] Developer Mailing List
The developer list is for Hive developers to discuss ongoing work, make
decisions, and vote on technical issues.Subscribe: dev-subscribe@hive.apache.orgPost: dev@hive.apache.orgUnsubscribe: dev-unsubscribe@hive.apache.orgArchives: Apache
[H2] Issues Mailing List
The issues list receives all notifications from the JIRA issue tracker.Subscribe: issues-subscribe@hive.apache.orgPost: issues@hive.apache.orgUnsubscribe: issues-unsubscribe@hive.apache.orgArchives: Apache
[H2] Commits Mailing List
The commits list receives notifications with diffs when changes are committed
to the Hive source tree.Subscribe: commits-subscribe@hive.apache.orgUnsubscribe: commits-unsubscribe@hive.apache.orgArchives: Apache
[H2] Security Mailing List
The security mailing list is a private list for discussion of potential security vulnerabilities issues. Please post potential security vulnerabilities to this list so that they may be investigated and fixed before the vulnerabilities is published.Note: This mailing list is NOT for end-user questions and discussion on security. Please use the user mailing list for such issues.The Hive security mailing list is : security@hive.apache.org.In order to post to the list, it is NOT necessary to first subscribe to it.
1705 chars
SUB-PAGE (https://hive.apache.org//docs/latest/) Documentation
[H1] REST Catalog Integration
[H2] Table of Contents
Hive + Gravitino + KeycloakArchitecture OverviewPrerequisitesQuickstartConfigurationKeyclockGravitinoHiveNetworking NotesHive + PolarisArchitecture OverviewPrerequisitesQuickstartConfigurationPolarisHiveNetworking Notes
[H2] Hive + Gravitino + Keycloak
The code for this setup is located in the Hive repository in packaging/src/docker/thirdparties/gravitino folder.It contains a docker-compose-based setup integrating Apache Hive, Gravitino Iceberg REST server, and Keycloak for OAuth2 authentication. It allows Hive to use an Iceberg REST catalog secured via Keycloak.
[H3] Architecture Overview
This diagram illustrates the key docker-compose components and their interactions in this setup:
[H1] Apache Hive : ChangeLog
[H2] Release 4.0.0 - 2024-03-29
[H3] NEW FEATURES:
JIRASummaryPriorityComponentReporterContributorHIVE-27850Iceberg: Major QB CompactionMajorIceberg integrationDmitriy FingermanDmitriy FingermanHIVE-26222Native GeoSpatial Support in HiveMajorHive, HiveServer2mahesh kumar beheraAyush SaxenaHIVE-27980Hive Iceberg Compaction: add support for OPTIMIZE TABLE syntaxMajor.Dmitriy FingermanDmitriy FingermanHIVE-26435Add method for collecting HMS meta summaryMajor.Ruyi ZhengHongdan Zhu
[H3] IMPROVEMENTS:
JIRASummaryPriorityComponentReporterContributorHIVE-26666Filter out compactions by id to minimise expense of db operationsMajor.KIRTI RUGEKIRTI RUGEHIVE-27563Add typeof UDFMinorUDFJohn ShermanJohn ShermanHIVE-27575MASK_HASH UDF generate a log per rowMajorUDFShohei OkumiyaShohei OkumiyaHIVE-27396Use -strict argument for Thrift code generation to prevent compatibility issuesMajorBuild InfrastructureJoe McDonnellJoe McDonnellHIVE-27554Validate URL used by SSO workflow for JDBC connectionMinorJDBCHenri BiestroHenri BiestroHIVE-27516Add programatically added DAG scoped properties to DAG ConfigurationMajor.László BodorLászló BodorHIVE-27586Parse dates from strings ignoring trailing (potentialy) invalid charsMajorHiveServer2Stamatis ZampetakisStamatis ZampetakisHIVE-27578Refactor genJoinRelNode to use genAllRexNode instead of genAllExprNodeDescMajor.Soumyakanti DasSoumyakanti DasHIVE-27600Reduce filesystem calls in OrcFileMergeOperatorMinorHiveYi ZhangYi ZhangHIVE-25576Configurable datetime formatter for unix_timestamp, from_unixtimeMajor.Ashish SharmaStamatis ZampetakisHIVE-27585Upgrade kryo serialization lib to latest versionMinorSerializers/DeserializersSuprith ChandrashekharacharSuprith ChandrashekharacharHIVE-27595Improve efficiency in the filtering hooksMinorHiveServer2Naveen GangamHenri BiestroHIVE-27645Clean test cases by refactoring assertFalse(equals()) using assertNotEquals & @Test(excepted) using assertThrowsMinor.Taher GhalebTaher GhalebHIVE-27599ConvertAstToSearchArg improvement with output and typo in commentsMajorServer InfrastructurexyxyHIVE-27627Iceberg: Insert into/overwrite partition supportMajor.Sourabh BadhyaSourabh BadhyaHIVE-27525Ease the write permissions on external table during create table operationMajorStandalone MetastoreSai Hemanth GantasalaRiju TrivediHIVE-27665Change Filter Parser on HMS to allow backticksMajorStandalone MetastoreSteve CarlinSteve CarlinHIVE-27461HiveMetaStoreAuthorizer should log the root cause of checkPrivilegesMajorHiveWecharWecharHIVE-27661Auth mode inferred from the Authorization headerMajorHiveServer2Gergely FarkasGergely FarkasHIVE-27309Large number of partitions and small files causes OOM in query coordinatorMajorIceberg integrationRajesh BalamohanDmitriy FingermanHIVE-27656Upgrade jansi.version to 2.4.0Major.Simhadri GovindappaSimhadri GovindappaHIVE-27673Configurable datetime formatter for date_formatMajorHiveServer2Stamatis ZampetakisStamatis ZampetakisHIVE-27664AlterTableSetLocationAnalyzer threw a confusing exception “Cannot connect to namenode”Major.xiongyinkexiongyinkeHIVE-27564Add log for ZooKeeperTokenStoreMajor.lvyanquanlvyanquanHIVE-27694Include HiveIcebergSerDe in default list of serdes using HMSMinorStandalone MetastoreNaveen GangamNaveen GangamHIVE-27696Docker build from source should include iceberg profileMajor.Ayush SaxenaAyush SaxenaHIVE-21100Allow flattening of table subdirectories resulted when using TEZ engine and UNION clauseMajor.George PachitariuAyush SaxenaHIVE-27646Iceberg: Retry query when concurrent write queries fail due to conflicting writesMajor.Simhadri GovindappaSimhadri GovindappaHIVE-27672Iceberg: Truncate partition supportMajor.Sourabh BadhyaSourabh BadhyaHIVE-27729Iceberg: Check Iceberg type in AlterTableExecuteAnalyzerMajorIceberg integrationButao ZhangButao ZhangHIVE-27406CompactionTxnHandler cleanupMajorHiveLászló VéghLászló VéghHIVE-27752Remove DagUtils duplicate classMinor.László BodorAkshat MathurHIVE-27757Upgrade hadoop to 3.3.6Major.Ayush SaxenaAyush SaxenaHIVE-27723Prevent localizing the same original file more than once if symlinks are presentMajor.László BodorLászló BodorHIVE-27771Iceberg: Allow expire snapshot by time rangeMajor.Ayush SaxenaAyush SaxenaHIVE-27755Quote identifiers in SQL emitted by SchemaTool for MySQLMajorStandalone MetastoreStamatis ZampetakisStamatis ZampetakisHIVE-27793Iceberg: Support setting current snapshot with SnapshotRefMajorIceberg integrationButao ZhangButao ZhangHIVE-27799Bump org.apache.zookeeper:zookeeper from 3.7.1 to 3.7.2Major.Ayush SaxenaHIVE-27182tez_union_with_udf.q with TestMiniTezCliDriver is flakyMajor.Ayush SaxenaStamatis ZampetakisHIVE-27686Use ORC 1.8.5.Major.Zoltán RátkaiZoltán RátkaiHIVE-27802Simplify TestTezSessionState.testSymlinkedLocalFilesAreLocalizedOnceMajor.László BodorLászló BodorHIVE-27786Iceberg: Eliminate engine.hive.enabled table propertyMajor.Ayush SaxenaAyush SaxenaHIVE-27346Getting exception for wildcard (*) search for database and table nameMajor.Hongdan ZhuHongdan ZhuHIVE-27731Perform metadata delete when only static filters are presentMajor.Sourabh BadhyaSourabh BadhyaHIVE-27826Upgrade to Parquet 1.13.1MajorParquetButao ZhangButao ZhangHIVE-27780Implement direct SQL for get_all_functionsMajorStandalone MetastoreButao ZhangButao ZhangHIVE-27825Better error message for an empty quoted identifierMinorParserShohei OkumiyaShohei OkumiyaHIVE-24815Remove “IDXS” Table from Metastore SchemaMajorMetastore, Standalone MetastoreHunter LoganRiju TrivediHIVE-27779Iceberg: Drop partition supportMajor.Sourabh BadhyaSourabh BadhyaHIVE-27789Iceberg: Add a way to expire snapshots with retain lastMajor.Ayush SaxenaAyush SaxenaHIVE-27593Iceberg: Keep iceberg properties in sync with hms propertiesMajorIceberg integrationButao ZhangButao ZhangHIVE-27864Update plugin for SBOM generation to 2.7.10Major.Vinod AnandanVinod AnandanHIVE-27762Don’t fall back to jdo query in ObjectStore if direct sql throws unrecoverable exceptionMajorHiveWecharWecharHIVE-27819Iceberg: Upgrade iceberg version to 1.4.2MajorIceberg integrationButao ZhangButao ZhangHIVE-27869Iceberg: Select on HadoopTable fails at HiveIcebergStorageHandler#canProvideColStatsMajorIceberg integrationButao ZhangButao ZhangHIVE-27828Iceberg integration: enable copy on write update when split update is onMajorIceberg integrationKrisztian KasaKrisztian KasaHIVE-27877Bump org.apache.avro:avro from 1.11.1 to 1.11.3Major.Ayush SaxenaHIVE-27889Bump org.apache.santuario:xmlsec from 2.3.0 to 2.3.4Major.Ayush SaxenaHIVE-27871Fix some formatting problems is YarnQueueHelperMajor.László BodorMahesh Raju SomalarajuHIVE-27896Remove common-lang usageMajor.Cheng PanCheng PanHIVE-27906Iceberg: Implement Delete Orphan FilesMajor.Ayush SaxenaAyush SaxenaHIVE-27912Include Iceberg module in nightly buildsMajor.Butao ZhangButao ZhangHIVE-27903Iceberg: Implement Expire Snapshot with default table propertiesMajorHiveJK PasimuthuAyush SaxenaHIVE-27633HMS: MTable to Table process reduces view related SQLMinorMetastoredzcxzldzcxzlHIVE-26630Introduce copy-on-write DML implementations for Iceberg tablesMajor.Ádám SzitaDenys KuzmenkoHIVE-27918Iceberg: Push transforms for clustering during table writesMajor.Sourabh BadhyaSourabh BadhyaHIVE-27894Enhance HMS Handler Logs for all ‘get_partition’ functions.Major.Shivangi JhaShivangi JhaHIVE-27905Some GenericUDFs wrongly cast ObjectInspectorsMajor.Shohei OkumiyaShohei OkumiyaHIVE-27935Add qtest for Avro invalid schema and field namesMajor.Akshat MathurAkshat MathurHIVE-27856Change the default value of hive.optimize.cte.materialize.threshold to -1Major.Seonggon NamgungSeonggon NamgungHIVE-27936Disable flaky test testBootstrapAcidTablesDuringIncrementalWithConcurrentWritesMajorTesting InfrastructureButao ZhangButao ZhangHIVE-27803Bump org.apache.avro:avro from 1.11.1 to 1.11.3Major.Ayush SaxenaHIVE-27934Fix incorrect description about the execution framework in README.mdMinor.Butao ZhangButao ZhangHIVE-27690Handle casting NULL literal to complex typeMajor.Krisztian KasaKrisztian KasaHIVE-27919Constant reduction in CBO does not work for FROM_UNIXTIME, DATE_ADD, DATE_SUB, TO_UNIX_TIMESTAMPMajorCBOStamatis ZampetakisStamatis ZampetakisHIVE-23558Remove compute_stats UDAFMajorStatisticsJesús Camacho RodríguezButao ZhangHIVE-27961Beeline will print duplicate stats info when hive.tez.exec.print.summary is trueMinor.Butao ZhangButao ZhangHIVE-27530Implement direct SQL for alter partitions to improve performanceMajor.WecharWecharHIVE-27925HiveConf: unify ConfVars enum and use underscore for better readabilityMajor.László BodorKokila NHIVE-27969Add verbose logging for schematool and metastore service for Docker containerMajor.Akshat MathurAkshat MathurHIVE-27978Tests in hive-unit module are not running againMajor.László BodorLászló BodorHIVE-27911Drop database query failing with Invalid ACL ExceptionMajor.KIRTI RUGEKIRTI RUGEHIVE-27937Clarifying comments and xml configs around tez container sizeMajor.László BodorLászló BodorHIVE-27977Fix ordering flakiness in TestHplSqlViaBeeLineMajor.László BodorLászló BodorHIVE-27023Add setting to disable hive session being started during Hive Cli startupMinor.Alagappan MaruthappanAlagappan MaruthappanHIVE-27827Improve performance of direct SQL implement for getPartitionsByFilterMajor.WecharWecharHIVE-27994Optimize renaming the partitioned tableMajor.Zhihua DengZhihua DengHIVE-27979HMS alter_partitions log adds table nameMinorStandalone MetastoredzcxzldzcxzlHIVE-28008ParquetFileReader is not closed in ParquetHiveSerDe.readSchemaMinorHiveMichal LorekMichal LorekHIVE-27991Utilise FanoutWriters when inserting records in an Iceberg table when the records are unsortedMajor.Sourabh BadhyaSourabh BadhyaHIVE-27984Support backward compatibility of hms thrift struct about column statsMajorStandalone MetastoreButao ZhangButao ZhangHIVE-27481TxnHandler cleanupMajorHiveLászló VéghLászló VéghHIVE-28038Disable fallback to jdo for DeadlineExceptionMajorHiveWecharWecharHIVE-27958Refactor DirectSqlUpdatePart classMajorHiveWecharWecharHIVE-27992Upgrade to tez 0.10.3Major.László BodorLászló BodorHIVE-26445Use tez.local.mode.without.network for qtestsMajor.László BodorLászló BodorHIVE-27022Split removeDuplicateCompletedTxnComponents away from AcidHouseKeeper and onto a separate timerMajor.Jason PhelpsTaraka Rama Rao LethavadlaHIVE-28071Sync jetty version across modulesMinor.Raghav AggarwalRaghav AggarwalHIVE-28015Iceberg: Add identifier-field-ids support in HiveMajorIceberg integrationDenys KuzmenkoButao ZhangHIVE-28081Code refine on ClearDanglingScratchDir::removeLocalTmpFilesTrivial.Butao ZhangButao ZhangHIVE-28064Add cause to ParseException for diagnosability purposesMajorParserStamatis ZampetakisStamatis ZampetakisHIVE-28056Bump com.jayway.jsonpath:json-path from 2.8.0 to 2.9.0Major.László BodorLászló BodorHIVE-28078TestTxnDbUtil should generate csv files when we query the metastore databaseMajorStandalone MetastoreZsolt MiskolcziZsolt MiskolcziHIVE-27692Explore removing the always task from embedded HMSMajorStandalone MetastoreZhihua DengZhihua DengHIVE-27405Throw out the detail error Invalid partition name to the clientsMajorHiveServer2Taraka Rama Rao LethavadlaTaraka Rama Rao LethavadlaHIVE-27845Upgrade protobuf to 3.24.4 to fix CVEsMajor.Akshat MathurtanishqchughHIVE-28080Propagate statistics from a source table to the materialized CTEMajorQuery PlanningShohei OkumiyaShohei OkumiyaHIVE-28090correct desc of hive.metastore.disallow.incompatible.col.type.changesMajor.zzzzming95zzzzming95HIVE-28083Enable HMS client/query cache for EXPLAIN queriesMinorHiveSoumyakanti DasSoumyakanti DasHIVE-25972HIVE_VECTORIZATION_USE_ROW_DESERIALIZE in hiveconf.java imply default value is false,in fact the default value is ’true’MajorConfiguration, HivelklKokila NHIVE-28093Re-execute DAG in case of NoCurrentDAGExceptionMajor.László BodorLászló BodorHIVE-28051LLAP: cleanup local folders on startup and periodicallyMajor.László BodorLászló Bodor
[H3] BUG FIXES:
JIRASummaryPriorityComponentReporterContributorHIVE-26837CTLT with hive.create.as.external.legacy as true creates managed table instead of external tableMajorHiveServer2Ramesh Kumar ThangarajanRamesh Kumar ThangarajanHIVE-27562Iceberg: Fetching virtual columns failingMajor.Ayush SaxenaAyush SaxenaHIVE-27487NPE in Hive JDBC storage handlerMajorJDBC storage handlerZhihua DengZhihua DengHIVE-27582Do not cache HBase table input format in FetchOperatorMajor.Ganesha ShreedharaGanesha ShreedharaHIVE-27304Exclude CTAS condition while forming storage handler url permissions in HS2 authorizer.MajorHiveSai Hemanth GantasalaSai Hemanth GantasalaHIVE-24771Fix hang of TransactionalKafkaWriterTestMajor.Zoltan HaindrichKokila NHIVE-27631Fix CCE when set fs.hdfs.impl other than DistributedFileSystemMajorHiveBaolong MaoBaolong MaoHIVE-22961Drop function in Hive should not send request for drop database to Ranger plugin.MajorHiveSam AnRiju TrivediHIVE-27463Non-daemon thread prevents HMS from exiting when failed to start thrift serverMinor.Zhihua DengZhihua DengHIVE-27536Merge task must be invoked after optimisation for external CTAS queriesMajor.Sourabh BadhyaSourabh BadhyaHIVE-27566Fix some yarn cluster options for testsMajor.László BodorLászló BodorHIVE-27632ClassCast Exception in Vectorization converting decimal64 to decimalMajorVectorizationRiju TrivediStephen CarlinHIVE-27539Drop renamed external table fails when hive.metastore.try.direct.sql.ddl is disabledMajor.Venugopal Reddy KVenugopal Reddy KHIVE-21213Acid table bootstrap replication needs to handle directory created by compaction with txn idMajorHive, HiveServer2, replmahesh kumar beheramahesh kumar beheraHIVE-27667Fix get partitions with max_partsMajorMetastoreYuming WangYuming WangHIVE-27657Change hive.fetch.task.conversion.threshold default valueMajor.Mayank KunwarMayank KunwarHIVE-26961Fix improper replication metric count when hive.repl.filter.transactions is set to true.Major.Rakshith CRakshith CHIVE-27642StartMiniHS2Cluster fails to run due to missing JDBC driver with PostgresMajorHiveServer2Zoltán RátkaiZoltán RátkaiHIVE-27643Exclude compaction queries from ranger policiesCritical.László VéghLászló VéghHIVE-17350metrics errors when retrying HS2 startupMajor
15000 chars
🛡️ Trust Signals — reviews, proof links, trust-theatre flag (Trust & Proof)
1Review mentions (all pages)
0External proof links (all pages)
PageReviewsProof links
/ (home) 0 0
//development/gettingstarted/ 0 0
//community/mailinglists/ 0 0
//docs/latest/ 1 0
🔗 Identity & Technical Layer — schema JSON-LD: identity chains, entity gaps (Identity & Authority)
Homepage — no schema detected (entity gap)
//development/gettingstarted/ — no schema detected (entity gap)
//community/mailinglists/ — no schema detected (entity gap)
//docs/latest/ — no schema detected (entity gap)

Your Diagnosis

Before revealing the machine’s verdict, predict the BS score for each signal. Higher = more BS (more fluff, less verifiable substance). Drag each slider, then submit to compare your judgment against the engine.

Information Density 0 / 30
Read the Narrative & headings: do hard facts (prices, dates, numbers) outweigh fluff power-words?
Semantic Coherence 0 / 20
Compare the homepage promise against the sub-page reality. Do they hold the same line?
Trust & Proof 0 / 20
Weigh review mentions against actual external proof links. Claims without verification = theatre.
Commodity Fingerprint 0 / 15
Check headings & narrative against the industry clichés in the setup above.
Identity & Authority 0 / 15
Inspect the schema: is there real Organization/Person identity with sameAs links, or gaps?
Your predicted BS score 0 / 100
💡 Stuck? Reveal the heuristic lens — how the deterministic page-auditor reads each signal (no AI, pure pattern rules)

These are the structural rules a local, deterministic auditor applies — the same lens you can use to judge each signal. They describe what to look for, not this company’s result.

Information Density

Classify each sentence as substantive or hollow. Grounding markers — numbers, currencies, dates, technical units, named entities — outweigh marketing adjectives. When fluff sits right next to hard evidence, the fluff is forgiven.

Semantic Alignment

Pull the main entities out of the H1, then check whether they actually recur through the body. A page that announces one thing and then talks about another drifts. Headings with no real sentences underneath read as pseudo-substance.

Trust & Proof

Count trust words (review, testimonial, rating, verified) against real outbound proof links (Google, Trustpilot, Clutch, G2, Yelp). Lots of trust language with zero verification links is trust theatre. Unlinked logo galleries count against it.

Commodity Fingerprint

Look at how much sentence length varies. Natural writing varies its rhythm; templated or mass-produced copy is statistically uniform. Very low variation reads as commodity content — unless unique named entities break the pattern.

Identity & Authority

Inspect the JSON-LD. Is there an Organization or Person schema, and does it carry sameAs links to real external profiles (LinkedIn, socials)? Missing schema or no identity declaration signals an anonymous entity.

Want to apply this lens yourself? The free BS Indicator Chrome extension runs these heuristic checks live on any page. Bear in mind it is a single-page, deterministic tool — it relies only on pattern rules for the page in front of it and does not perform the cross-page semantic correlation this audit uses, so its readout is a starting lens, not the full verdict.

B
BS Level
Software, SaaS & Tech Products
33.2 Avg BS

Based on 1130 businesses audited.

BS Detector

Software, SaaS & Tech Products BS: Apache Hive (hive.apache.org)

https://hive.apache.org 📍 Industry: Software, SaaS & Tech Products
12 BS / 100

This is a high-substance technical site that treats its audience as engineers rather than ‘decision-makers’. It completely eschews the ‘all-in-one platform’ fluff common in SaaS, providing instead a forensic record of its own development. It is the antithesis of a bullshit-heavy marketing site.

Info Density Power-words vs. Substance ratio.
4
13% BS
Semantic Coherence Homepage promise vs. Sub-page reality.
0
0% BS
Trust & Proof Verifiable evidence vs. Trust Theatre.
2
10% BS
Commodity Fingerprint Detection of industry clichés/templates.
3
20% BS
Identity & Authority Expert verifiability & Schema depth.
3
20% BS

Implement Organization and SoftwareApplication schema.org structured data to formalize the brand identity for search engines. Add a ‘Powered By’ page that expands the current logo cloud into brief technical case studies to ground the ‘1000+ deployments’ claim. Update the copyright year and ensure all release dates are explicitly listed next to version numbers to maintain temporal authority. Include a status page or uptime link for the public-facing services like the JIRA tracker and Mailing list archives.

The website perfectly aligns with the Big Data and Enterprise Software industry. The content focuses exclusively on distributed data warehousing, SQL-on-Hadoop, and metadata management, providing deep technical specifications rather than surface-level marketing.

“The score of 12 is driven by the technical implementation gaps (missing schema) and minor use of industry jargon. The site's information density and semantic coherence are nearly perfect, effectively neutralizing the common BS patterns found in commercial software websites.”

Verified Analysis Date: May 27, 2026 © 1EuroSEO Independent Evaluator — Non-Sponsored Result
Brand AI Reputation