Best Data Warehouse Software for Apache Hive
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Compare the Top Data Warehouse Software that integrates with Apache Hive as of November 2025
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This a list of Data Warehouse software that integrates with Apache Hive. Use the filters on the left to add additional filters for products that have integrations with Apache Hive. View the products that work with Apache Hive in the table below.
What is Data Warehouse Software for Apache Hive?
Data warehouse software helps organizations store, manage, and analyze large volumes of data from different sources in a centralized, structured repository. These systems support the extraction, transformation, and loading (ETL) of data from multiple databases and applications into the warehouse, ensuring that the data is cleaned, formatted, and organized for business intelligence and analytics purposes. Data warehouse software typically includes features such as data integration, querying, reporting, and advanced analytics to help businesses derive insights from historical data. It is commonly used for decision-making, forecasting, and performance tracking, making it essential for industries like finance, healthcare, retail, and manufacturing. Compare and read user reviews of the best Data Warehouse software for Apache Hive currently available using the table below. This list is updated regularly.
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ClicData
ClicData
ClicData is the world first 100% cloud-based Business Intelligence and data management software. With our included data warehouse, you can easily cleanse, combine, transform and merge any data from any data source. Create interactive and self-updated dashboards that you can share with your Manager, your team or customers in multiple ways: email delivery schedule, export or even dynamic dashboards via our LiveLinks. With ClicData, automate everything from data connection, data refresh and management, and scheduling routines.Starting Price: $25.00/month -
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Apache Doris
The Apache Software Foundation
Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.Starting Price: Free -
3
Stackable
Stackable
The Stackable data platform was designed with openness and flexibility in mind. It provides you with a curated selection of the best open source data apps like Apache Kafka, Apache Druid, Trino, and Apache Spark. While other current offerings either push their proprietary solutions or deepen vendor lock-in, Stackable takes a different approach. All data apps work together seamlessly and can be added or removed in no time. Based on Kubernetes, it runs everywhere, on-prem or in the cloud. stackablectl and a Kubernetes cluster are all you need to run your first stackable data platform. Within minutes, you will be ready to start working with your data. Configure your one-line startup command right here. Similar to kubectl, stackablectl is designed to easily interface with the Stackable Data Platform. Use the command line utility to deploy and manage stackable data apps on Kubernetes. With stackablectl, you can create, delete, and update components.Starting Price: Free -
4
Vaultspeed
VaultSpeed
Experience faster data warehouse automation. The Vaultspeed automation tool is built on the Data Vault 2.0 standard and a decade of hands-on experience in data integration projects. Get support for all Data Vault 2.0 objects and implementation options. Generate quality code fast for all scenarios in a Data Vault 2.0 integration system. Plug Vaultspeed into your current set-up and leverage your investments in tools and knowledge. Get guaranteed compliance with the latest Data Vault 2.0 standard. We are in continuous interaction with Scalefree, the body of knowledge for the Data Vault 2.0 community. The Data Vault 2.0 modelling approach strips the model components to their bare minimum so they can be loaded through the same loading pattern (repeatable pattern) and have the same database structure. Vaultspeed works with a template system, which understands the structure of the object types, and easy-to-set configuration parameters.Starting Price: €600 per user per month -
5
Lyftrondata
Lyftrondata
Whether you want to build a governed delta lake, data warehouse, or simply want to migrate from your traditional database to a modern cloud data warehouse, do it all with Lyftrondata. Simply create and manage all of your data workloads on one platform by automatically building your pipeline and warehouse. Analyze it instantly with ANSI SQL, BI/ML tools, and share it without worrying about writing any custom code. Boost the productivity of your data professionals and shorten your time to value. Define, categorize, and find all data sets in one place. Share these data sets with other experts with zero codings and drive data-driven insights. This data sharing ability is perfect for companies that want to store their data once, share it with other experts, and use it multiple times, now and in the future. Define dataset, apply SQL transformations or simply migrate your SQL data processing logic to any cloud data warehouse. -
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IBM watsonx.data
IBM
Put your data to work, wherever it resides, with the open, hybrid data lakehouse for AI and analytics. Connect your data from anywhere, in any format, and access through a single point of entry with a shared metadata layer. Optimize workloads for price and performance by pairing the right workloads with the right query engine. Embed natural-language semantic search without the need for SQL, so you can unlock generative AI insights faster. Manage and prepare trusted data to improve the relevance and precision of your AI applications. Use all your data, everywhere. With the speed of a data warehouse, the flexibility of a data lake, and special features to support AI, watsonx.data can help you scale AI and analytics across your business. Choose the right engines for your workloads. Flexibly manage cost, performance, and capability with access to multiple open engines including Presto, Presto C++, Spark Milvus, and more. -
7
Cloudera Data Warehouse
Cloudera
Cloudera Data Warehouse is a cloud-native, self-service analytics solution that lets IT rapidly deliver query capabilities to BI analysts, enabling users to go from zero to query in minutes. It supports all data types, structured, semi-structured, unstructured, real-time, and batch, and scales cost-effectively from gigabytes to petabytes. It is fully integrated with streaming, data engineering, and AI services, and enforces a unified security, governance, and metadata framework across private, public, or hybrid cloud deployments. Each virtual warehouse (data warehouse or mart) is isolated and automatically configured and optimized, ensuring that workloads do not interfere with each other. Cloudera leverages open source engines such as Hive, Impala, Kudu, and Druid, along with tools like Hue and more, to handle diverse analytics, from dashboards and operational analytics to research and discovery over vast event or time-series data. -
8
CelerData Cloud
CelerData
CelerData is a high-performance SQL engine built to power analytics directly on data lakehouses, eliminating the need for traditional data‐warehouse ingestion pipelines. It delivers sub-second query performance at scale, supports on-the‐fly JOINs without costly denormalization, and simplifies architecture by allowing users to run demanding workloads on open format tables. Built on the open source engine StarRocks, the platform outperforms legacy query engines like Trino, ClickHouse, and Apache Druid in latency, concurrency, and cost-efficiency. With a cloud-managed service that runs in your own VPC, you retain infrastructure control and data ownership while CelerData handles maintenance and optimization. The platform is positioned to power real-time OLAP, business intelligence, and customer-facing analytics use cases and is trusted by enterprise customers (including names such as Pinterest, Coinbase, and Fanatics) who have achieved significant latency reductions and cost savings. -
9
Data Virtuality
Data Virtuality
Connect and centralize data. Transform your existing data landscape into a flexible data powerhouse. Data Virtuality is a data integration platform for instant data access, easy data centralization and data governance. Our Logical Data Warehouse solution combines data virtualization and materialization for the highest possible performance. Build your single source of data truth with a virtual layer on top of your existing data environment for high data quality, data governance, and fast time-to-market. Hosted in the cloud or on-premises. Data Virtuality has 3 modules: Pipes, Pipes Professional, and Logical Data Warehouse. Cut down your development time by up to 80%. Access any data in minutes and automate data workflows using SQL. Use Rapid BI Prototyping for significantly faster time-to-market. Ensure data quality for accurate, complete, and consistent data. Use metadata repositories to improve master data management. -
10
Apache Kylin
Apache Software Foundation
Apache Kylin™ is an open source, distributed Analytical Data Warehouse for Big Data; it was designed to provide OLAP (Online Analytical Processing) capability in the big data era. By renovating the multi-dimensional cube and precalculation technology on Hadoop and Spark, Kylin is able to achieve near constant query speed regardless of the ever-growing data volume. Reducing query latency from minutes to sub-second, Kylin brings online analytics back to big data. Kylin can analyze 10+ billions of rows in less than a second. No more waiting on reports for critical decisions. Kylin connects data on Hadoop to BI tools like Tableau, PowerBI/Excel, MSTR, QlikSense, Hue and SuperSet, making the BI on Hadoop faster than ever. As an Analytical Data Warehouse, Kylin offers ANSI SQL on Hadoop/Spark and supports most ANSI SQL query functions. Kylin can support thousands of interactive queries at the same time, thanks to the low resource consumption of each query. -
11
Apache Hudi
Apache Corporation
Hudi is a rich platform to build streaming data lakes with incremental data pipelines on a self-managing database layer, while being optimized for lake engines and regular batch processing. Hudi maintains a timeline of all actions performed on the table at different instants of time that helps provide instantaneous views of the table, while also efficiently supporting retrieval of data in the order of arrival. A Hudi instant consists of the following components. Hudi provides efficient upserts, by mapping a given hoodie key consistently to a file id, via an indexing mechanism. This mapping between record key and file group/file id, never changes once the first version of a record has been written to a file. In short, the mapped file group contains all versions of a group of records. -
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e6data
e6data
Limited competition due to deep barriers to entry, specialized know-how, massive capital needs, and long time-to-market. Existing platforms are indistinguishable in price, and performance reducing the incentive to switch. Migrating from one engine’s SQL dialect to another engine’s SQL involves months of effort. Truly format-neutral computing, interoperable with all major open standards. Enterprise data leaders are hit by an unprecedented explosion in computing demand for data intelligence. They are surprised to find that 10% of their heavy, compute-intensive use cases consume 80% of the cost, engineering effort and stakeholder complaints. Unfortunately, such workloads are also mission-critical and non-discretionary. e6data amplifies ROI on enterprises' existing data platforms and architecture. e6data’s truly format-neutral compute has the unique distinction of being equally efficient and performant across leading data lakehouse table formats.
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