HIVE PROJECTS
Apache Hive is an open-source distributed data warehouse project under the Apache Software Foundation, providing SQL-based petabyte-scale analytics built on Hadoop for enterprise data lake and lakehouse workloads.
- Company typePrivate
- Founded2008
- Headquarters—
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
What HIVE PROJECTS does
Apache Hive is an open-source distributed data warehouse project under the Apache Software Foundation, originally developed at Facebook in 2008 and donated to the ASF. It provides a SQL-like query interface (HiveQL) for batch analytics over petabyte-scale datasets stored in Hadoop Distributed File System and cloud object stores (S3, ADLS, GCS). Core components include HiveServer2 (the query execution service), the Hive Metastore (the central schema and metadata catalog), HCatalog, WebHCat, the Beeline CLI, and LLAP (Low Latency Analytics Processing) for interactive query performance. The project supports ACID transactions, cost-based optimization via Apache Calcite, and integration with execution engines including Tez, Spark, MapReduce, and Presto. With 18+ years of development and 1000+ enterprise deployments, Hive serves as foundational data infrastructure for organizations operating large-scale data lakes, with major cloud providers (AWS via EMR, Microsoft via Azure HDInsight, Google Cloud via Dataproc Metastore) integrating the Hive Metastore as a standard metadata layer.
The project's business model is open-source under the Apache 2.0 license, generating no direct revenue. Economic value is captured downstream by cloud providers that offer managed Hive-compatible services, and by commercial vendors (Cloudera, Databricks, Treasure Data) that package Hive within proprietary distributions. The Hive Metastore has become a de facto standard open catalog for the lakehouse architecture, particularly through its integration with Apache Iceberg. The firmographic data references an entity called HIVE PROJECTS with 6 employees located in Rochdale, Lancashire, which appears to be a separate or ambiguously linked entity from the Apache Hive open-source project; the data does not clarify the relationship between the two. Based on available evidence, the project itself is community-driven with no commercial revenue stream, and any investment thesis must be evaluated against the open-source charter rather than a traditional company structure.
HIVE PROJECTS firmographics
Firmographics- Name
- HIVE PROJECTS
- Legal name
- Apache Software Foundation
- Website
- https://hive.apache.org
- Company type
- Private
- Founded year
- 2008
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Short description
- Apache Hive is an open-source distributed data warehouse project under the Apache Software Foundation, providing SQL-based petabyte-scale analytics built on Hadoop for enterprise data lake and lakehouse workloads.
- Ownership category
- akta.pro rank
HIVE PROJECTS industry classification
Industry- Product category
- Distributed Data Warehouse / Big Data SQL Analytics
- NAICS
- Computer Systems Design and Related Services (54151)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- Database Tools & Ecosystem (Replication, Backup/Recovery, HA/DR, Monitoring) (HDAEAAAO)
- akta.pro secondary industries
- Hybrid Cloud Management, Monitoring & FinOps (HDABAMAD), Cloud-Native Development (Containers, Kubernetes, Microservices) (BPAEACAD)
Keywords
HIVE PROJECTS business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Infrastructure, Technology or R&D, Operations, Others
Revenue model
- Open Source Distribution: Apache Hive is released under the Apache License v2 as an open-source project. There is no direct revenue generation; the project is maintained by volunteer contributors and organizations that use Hive commercially.
Go-to-market motion1 record
Distribution channels4 records
Marketing channels4 records
HIVE PROJECTS product offering
Product offeringCore offering
Apache Hive is a distributed, fault-tolerant data warehouse system built on Apache Hadoop that enables SQL-based analytics at petabyte scale. It facilitates reading, writing, and managing petabytes of data across distributed storage using SQL, with a central Hive Metastore (HMS) shared by Hive, Spark, and Impala. The project is released under the Apache License v2 and distributed via official ASF downloads, GitHub, Docker Hub, and Maven.
Product overview
Apache Hive is a distributed, fault-tolerant data warehouse system built on Apache Hadoop. The core product enables analytics at massive scale with petabyte-level data processing using familiar SQL syntax. The product ecosystem includes Hive Metastore (HMS) as the central metadata repository shared with Impala and Spark, HiveServer2 (HS2) providing JDBC/ODBC connectivity, Beeline as the primary CLI tool, and LLAP for low-latency interactive analytics. HCatalog provides table and storage management, while WebHCat offers REST API access. Hive supports multiple execution engines (Tez, MapReduce legacy), various cloud storage backends (S3, ADLS, GCS), and file formats including Parquet and ORC with ACID support. Version 4.x introduced deep Apache Iceberg integration for modern data lake architectures.
Differentiator
Problem solved
Functional benefit
Products and services
- Apache Hive Distributed, fault-tolerant data warehouse system that enables analytics at massive scale and facilitates reading, writing, and managing petabytes of data residing in distributed storage using SQL. Built on Apache Hadoop, targeted at enterprise data engineering and analytics teams.
- Hive Metastore (HMS) 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.
- HiveServer2 (HS2) Server component supporting 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.
- HCatalog
Quantifiable outcome
- Petabyte-scale data processing in production environments
- +2 more outcomes
Companies that use HIVE PROJECTS
Customer profileNamed customers6 records
Segments3 records
Ideal customer profiles3 records
HIVE PROJECTS technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration22 records
AI capability2 records
Feature9 records
HIVE PROJECTS partnerships and signals
Strategic signalPartnerships
Eleven partnerships are on record, tiered core and major.
- ClouderacoreCloudera's data platform incorporates Apache Hive and has historically been one of the largest commercial supporters of Hive development. The relationship demonstrates ecosystem integration where Cloudera provides enterprise-grade Hive distributions.
- Amazon Web Services (AWS)coreAWS EMR (Elastic MapReduce) provides native support for Apache Hive, enabling customers to run Hive-based analytics on AWS cloud infrastructure with S3 storage integration.
- Microsoft AzurecoreAzure HDInsight integrates Apache Hive as a core component for enterprise Hadoop analytics workloads in Microsoft Azure cloud environment.
- Google CloudcoreGoogle Cloud Dataproc Metastore supports Apache Hive integration, allowing users to leverage Hive Metastore for unified metadata management in GCP.
- DatabrickscoreDatabricks supports Apache Hive integration, enabling compatibility with Hive tables and metastore for users combining Databricks and Hive in their data workflows.
- Apache SparkcoreHive integrates seamlessly with Spark as a data source/sink, allowing Spark jobs to read and write data to Hive tables and leverage the Hive Metastore.
- Apache CalcitecoreHive utilizes Apache Calcite's cost-based query optimizer (CBO) for automatic SQL query optimization and optimal performance.
- Apache RangermajorHive integrates with Apache Ranger for fine-grained authorization and access control, providing enterprise security capabilities.
- Apache AtlasmajorHive integrates with Apache Atlas for data lineage tracking and governance capabilities, essential for enterprise compliance.
- Apache IcebergcoreHive provides out-of-the-box support for Apache Iceberg tables as a StorageHandler, enabling cloud-native, high-performance open table format for modern data lake architectures.
- Apache TezcoreHive supports Apache Tez as an execution engine, providing improved performance for interactive and batch processing workloads.
Scale indicators3 records
Recent moves5 records
Expansion highlights4 records
HIVE PROJECTS competitors and assessment
Company assessmentBroad incumbents
- Databricks: Commercial lakehouse platform built on Spark and Delta Lake that supports Hive Metastore compatibility. Offers a managed, cloud-native alternative that overlaps with Hive's enterprise SQL-on-data-lake use cases.
- Google BigQuery: Serverless cloud data warehouse from Google Cloud. Direct alternative for petabyte-scale SQL analytics workloads, with stronger cloud-native economics and zero-ops management.
- Amazon Redshift: AWS-managed cloud data warehouse offering. Competes with Hive-on-EMR for SQL analytics workloads in the AWS ecosystem with a columnar MPP architecture.
- Snowflake: Cloud-native data warehouse platform with broad enterprise adoption. Competes for the same SQL analytics workloads that historically ran on Hive, with a managed, decoupled-storage architecture.
Emerging players
- ClickHouse: Open-source columnar OLAP database with strong SQL support. Emerging alternative for sub-second analytical queries at scale, particularly for real-time analytics use cases that overlap with Hive LLAP.
- Dremio: Open lakehouse platform providing SQL query capabilities over Iceberg, Parquet, and other data lake formats. Competes in the modern data lake SQL analytics space that Hive 4.x is repositioning for.
- Starburst (Trino-based commercial distribution): Commercial enterprise distribution of Trino targeting data lakehouse SQL workloads. Offers a managed, vendor-supported alternative to open-source Trino for Hive-compatible petabyte-scale analytics.
Direct peers
- Apache Spark: Unified analytics engine that natively integrates with Hive Metastore and Hive tables. Comparable distributed data processing platform, often used alongside or as an alternative to Hive.
- Trino (formerly PrestoSQL): Open-source distributed SQL query engine for big data that runs against Hive Metastore, HDFS, S3, and Iceberg. Directly comparable SQL-on-Hadoop architecture and overlapping use cases for petabyte-scale analytics.
- Apache Impala: Apache-licensed MPP SQL query engine for Hadoop that shares the Hive Metastore. Direct peer for low-latency SQL-on-Hadoop workloads at petabyte scale.
Market position
Strengths4 records
Weaknesses4 records
Competitive moat5 records
Key risks5 records
Key highlights6 records
Customer concentration
HIVE PROJECTS social profiles
Digital presenceHIVE PROJECTS financial estimates
Financial estimateRevenue estimate
Valuation estimate
HIVE PROJECTS leadership team
Management profileNumber of profiles
HIVE PROJECTS funding detail
Funding detailFunding overview
Funding rounds
Investors
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HIVE PROJECTS M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about HIVE PROJECTS
What does HIVE PROJECTS do?
Apache Hive is a distributed, fault-tolerant data warehouse system built on Apache Hadoop that enables SQL-based analytics at petabyte scale. It facilitates reading, writing, and managing petabytes of data across distributed storage using SQL, with a central Hive Metastore (HMS) shared by Hive, Spark, and Impala. The project is released under the Apache License v2 and distributed via official ASF downloads, GitHub, Docker Hub, and Maven.
Is HIVE PROJECTS a public or private company?
HIVE PROJECTS is a private company. It is classified as nonprofit foundation owned and is currently operating.
When was HIVE PROJECTS founded?
HIVE PROJECTS was founded in 2008. It employs 1 to 10 people.
How does HIVE PROJECTS make money?
One revenue line is on record: open Source Distribution.
Who are HIVE PROJECTS's main competitors?
Broad incumbents on record are Databricks, Google BigQuery, Amazon Redshift and Snowflake. Emerging players are ClickHouse, Dremio and Starburst (Trino-based commercial distribution). Direct peers are Apache Spark, Trino (formerly PrestoSQL) and Apache Impala.
Does HIVE PROJECTS have an API?
Yes. HiveServer2 provides JDBC and ODBC APIs for integration with business intelligence tools and applications. WebHCat provides a REST API for HCatalog operations including running Hadoop MapReduce, Pig, and Hive jobs, as well as metadata operations. HMS (Hive Metastore) provides a Thrift API for metastore service access. Developer documentation is at hive.apache.org/docs/latest.
What industry is HIVE PROJECTS in?
HIVE PROJECTS's product category is Distributed Data Warehouse / Big Data SQL Analytics. Its primary akta.pro industry code is HDAEAAAO, Database Tools & Ecosystem (Replication, Backup/Recovery, HA/DR, Monitoring), with a secondary code of HDABAMAD, Hybrid Cloud Management, Monitoring & FinOps. Its NAICS code is 54151 and its SIC code is 7372.