Alternatives to Google Cloud BigQuery
Compare Google Cloud BigQuery alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Google Cloud BigQuery in 2026. Compare features, ratings, user reviews, pricing, and more from Google Cloud BigQuery competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
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Google Cloud SQL
Google
Fully managed relational database service for MySQL, PostgreSQL, and SQL Server with rich extension collections, configuration flags, and developer ecosystems. New customers get $300 in free credits to spend on Cloud SQL. You won’t be charged until you upgrade. Reduce maintenance costs with fully managed MySQL, PostgreSQL and SQL Server databases. Ensure business continuity with reliable and secure services backed by 24/7 SRE team. Data encryption at rest and in transit. Private connectivity with Virtual Private Cloud and user-controlled network access with firewall protection. Compliant with SSAE 16, ISO 27001, PCI DSS, and HIPAA. Scale your instances effortlessly with a single API call whether you start with simple testing or you need a highly available database in production. Simplify database operations with AI-powered assistance in Gemini, now in preview on Cloud SQL. It streamlines development, performance optimization, fleet management, governance, and migration. -
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DataBuck
FirstEigen
DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world. -
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AnalyticsCreator
AnalyticsCreator
AnalyticsCreator is a metadata-driven data warehouse automation application for teams working in the Microsoft data ecosystem. It enables data engineers to design, generate, and maintain production-ready data products across Microsoft SQL Server, Azure Data Factory, and Microsoft Fabric. By using centralized metadata, AnalyticsCreator generates ELT pipelines, dimensional models, historization logic, and analytical models in a consistent, version-controlled way. This reduces manual implementation effort and tool sprawl while ensuring transparency through built-in lineage tracking and clear visibility into data dependencies and change impact. With CI/CD integration via Azure DevOps and GitHub, plus support for custom SQL, AnalyticsCreator helps data teams scale delivery, enforce standards, and maintain control as complexity grows. -
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IBM Cognos Analytics acts as your trusted co-pilot for business with the aim of making you smarter, faster, and more confident in your data-driven decisions. IBM Cognos Analytics gives every user — whether data scientist, business analyst or non-IT specialist — more power to perform relevant analysis in a way that ties back to organizational objectives. It shortens each user’s journey from simple to sophisticated analytics, allowing them to harness data to explore the unknown, identify new relationships, get a deeper understanding of outcomes and challenge the status quo. Visualize, analyze and share actionable insights about your data with anyone in your organization with IBM Cognos Analytics.
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Domo
Domo
Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results. -
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StarTree
StarTree
StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.Starting Price: Free -
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Composable DataOps Platform
Composable Analytics
Composable is an enterprise-grade DataOps platform built for business users that want to architect data intelligence solutions and deliver operational data-driven products leveraging disparate data sources, live feeds, and event data regardless of the format or structure of the data. With a modern, intuitive dataflow visual designer, built-in services to facilitate data engineering, and a composable architecture that enables abstraction and integration of any software or analytical approach, Composable is the leading integrated development environment to discover, manage, transform and analyze enterprise data.Starting Price: $8/hr - pay-as-you-go -
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Amazon Redshift
Amazon
Amazon Redshift is a cloud-based data warehouse solution from AWS designed to deliver high-performance analytics and support modern AI-driven workloads. The platform enables organizations to analyze large volumes of structured and unstructured data across data warehouses, data lakes, and third-party sources using SQL. Redshift is built for scalability and cost efficiency, offering improved throughput and price-performance with AWS Graviton-powered RG instances and Redshift Serverless options. The solution also supports near real-time analytics through zero-ETL integrations that connect operational databases, streaming services, and enterprise applications without complex data pipelines. Amazon Redshift integrates with Amazon SageMaker and Amazon Bedrock to support advanced machine learning, analytics, and generative AI use cases.Starting Price: $0.543 per hour -
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Amazon Athena
Amazon
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets. Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a unified metadata repository across various services, crawl data sources to discover schemas and populate your Catalog with new and modified table and partition definitions, and maintain schema versioning. -
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Apache Pinot
Apache Corporation
Pinot is designed to answer OLAP queries with low latency on immutable data. Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index. Joins are currently not supported, but this problem can be overcome by using Trino or PrestoDB for querying. SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data. Consist of of both offline and real-time table. Use real-time table only to cover segments for which offline data may not be available yet. Detect the right anomalies by customizing anomaly detect flow and notification flow. -
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ClickHouse
ClickHouse
ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. ClickHouse's performance exceeds comparable column-oriented database management systems currently available on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. -
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Databricks
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
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GeoSpock
GeoSpock
GeoSpock enables data fusion for the connected world with GeoSpock DB – the space-time analytics database. GeoSpock DB is a unique, cloud-native database optimised for querying for real-world use cases, able to fuse multiple sources of Internet of Things (IoT) data together to unlock its full value, whilst simultaneously reducing complexity and cost. GeoSpock DB enables efficient storage, data fusion, and rapid programmatic access to data, and allows you to run ANSI SQL queries and connect to analytics tools via JDBC/ODBC connectors. Users are able to perform analysis and share insights using familiar toolsets, with support for common BI tools (such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™), and Data Science and Machine Learning environments (including Python Notebooks and Apache Spark). The database can also be integrated with internal applications and web services – with compatibility for open-source and visualisation libraries such as Kepler and Cesium.js. -
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Google Cloud Analytics Hub
Google
Google Cloud's Analytics Hub is a data exchange platform that enables organizations to efficiently and securely share data assets across organizational boundaries, addressing challenges related to data reliability and cost. Built on the scalability and flexibility of BigQuery, it allows users to curate a library of internal and external assets, including unique datasets like Google Trends. Analytics Hub facilitates the publication, discovery, and subscription to data exchanges without the need to move data, streamlining the accessibility of data and analytics assets. It also provides privacy-safe, secure data sharing with governance, incorporating in-depth governance, encryption, and security features from BigQuery, Cloud IAM, and VPC Security Controls. By leveraging Analytics Hub, organizations can increase the return on investment of data initiatives by exchanging data. Analytics Hub is based on the scalability and flexibility of BigQuery. -
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IBM Db2 Big SQL
IBM
A hybrid SQL-on-Hadoop engine delivering advanced, security-rich data query across enterprise big data sources, including Hadoop, object storage and data warehouses. IBM Db2 Big SQL is an enterprise-grade, hybrid ANSI-compliant SQL-on-Hadoop engine, delivering massively parallel processing (MPP) and advanced data query. Db2 Big SQL offers a single database connection or query for disparate sources such as Hadoop HDFS and WebHDFS, RDMS, NoSQL databases, and object stores. Benefit from low latency, high performance, data security, SQL compatibility, and federation capabilities to do ad hoc and complex queries. Db2 Big SQL is now available in 2 variations. It can be integrated with Cloudera Data Platform, or accessed as a cloud-native service on the IBM Cloud Pak® for Data platform. Access and analyze data and perform queries on batch and real-time data across sources, like Hadoop, object stores and data warehouses. -
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Knowledge Catalog is an AI-powered data catalog from Google Cloud that helps organizations manage and understand their entire data ecosystem. It automatically extracts semantics from both structured and unstructured data to build a dynamic context graph. This enables better data discovery, governance, and context-aware insights across the enterprise. The platform helps reduce AI hallucinations by grounding models in accurate, enterprise-specific data. It provides tools for tracking data lineage, profiling data, and measuring data quality. Users can also create business glossaries and enrich metadata to improve data usability. Knowledge Catalog integrates with various Google Cloud services and supports both analytics and AI-driven workflows. Overall, it enhances data visibility, governance, and trust across organizations.Starting Price: $0.060 per hour
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Google Cloud Spanner
Google
Scale as needed with no limits: Globally distributed, ACID-compliant database that automatically handles replicas, sharding, and transaction processing, so you can quickly scale to meet any usage pattern and ensure the success of your products. Cloud Spanner is built on Google’s dedicated network and battle-tested by Google services used by billions. It offers up to 99.999% availability with zero downtime for planned maintenance and schema changes. Do fewer thankless tasks with a simpler experience: IT Admins and DBAs are inundated with operating databases. With Cloud Spanner, creating or scaling a globally replicated database now takes a handful of clicks and reduces your cost of maintaining databases. -
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Keboola
Keboola
Keboola is a serverless integration Hub for data/people and AI models. We provide a cloud-based data integration platform that is designed to support the entire workflow from data extraction, cleaning, warehousing, enrichment, to ML based predictions and loading. The whole platform is highly collaborative and solves the biggest hurdles of "IT" based solutions. Our seamless one click UI will take even the novice business users from data acquisition to building model in Python in a matter of minutes. Try us out! You will love the experience :)Starting Price: Freemium -
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InDriver
ANDSystems
InDriver: A multi-functional JavaScript-based Automation Engine that allows you to perform multiple tasks simultaneously. InStudio: GUI application for remote InDriver configuration across multiple computers. Easily transforms setups into tailored solutions with minimal JS code and a few clicks. Copy-paste examples are readily available for quick integration. Key Applications: Data Automation and Integration Engine Conduct Extract-Transform-Load (ETL) operations effortlessly. Streamlines access to RESTful API resources, simplifying request definition, interval setting, JSON data processing, and database log-ins. Industrial Automation Engine Seamless interfacing with PLCs, sensors, and diverse devices. Read/write data, create control algorithms, and process data for SCADA, MES, and other systems. Database Automation Schedule queries for specific intervals or events, ensuring continuous automation.Starting Price: €1/day -
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Redash
Redash
Connect and query your data sources, build dashboards to visualize data and share them with your company. Enjoy the power and comfort of a SQL client with the collaborative advantages of a cloud based service. Easily visualize your results in various formats: chart, cohort, pivot table, boxplot, map, counter, sankey, sunburst and word cloud. Share your data-story with colleagues, other teams or external partners. Access Redash via API and extend its functionality as you like. SSO, access control and many other great features for enterprise-friendly workflow.Starting Price: $29 per month -
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Vertica
Rocket Software
Vertica is an enterprise-grade analytics database platform designed to help organizations run high-performance analytics, data warehousing, and AI workloads across hybrid cloud environments. Following its acquisition by Rocket Software, Vertica now strengthens Rocket’s modernization and enterprise data portfolio by combining advanced analytics, AI capabilities, and trusted mission-critical systems. The platform enables businesses to process and analyze massive volumes of structured and unstructured data while supporting on-premises, cloud, private cloud, and hybrid deployments. Vertica helps enterprises accelerate decision-making, modernize legacy environments, and run advanced analytics and generative AI directly on trusted enterprise data sources. The platform integrates with Rocket DataEdge and Rocket ContentEdge solutions to create a unified data modernization ecosystem focused on governance, analytics, and operational intelligence. -
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Trino
Trino
Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.Starting Price: Free -
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Panoply
SQream
Panoply brings together a managed data warehouse with included, pre-built ELT data connectors, making it the easiest way to store, sync, and access all your business data. Our cloud data warehouse (built on Redshift or BigQuery), along with built-in data integrations to all major CRMs, databases, file systems, ad networks, web analytics tools, and more, will have you accessing usable data in less time, with a lower total cost of ownership. One platform with one easy price is all you need to get your business data up and running today. Panoply gives you unlimited access to data sources with prebuilt Snap Connectors and a Flex Connector that can bring in data from nearly any RestAPI. Panoply can be set up in minutes, requires zero ongoing maintenance, and provides online support including access to experienced data architects.Starting Price: $299 per month -
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Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2/credit -
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Azure Synapse Analytics
Microsoft
Azure Synapse is Azure SQL Data Warehouse evolved. Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources—at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs. -
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Prophecy
Prophecy.ai
Prophecy is an AI-powered data preparation and analysis platform that enables business users to transform raw data into actionable insights through natural language prompts. The platform uses specialized AI agents to automatically generate visual, low-code data workflows that users can inspect, refine, validate, and deploy without requiring programming expertise. Prophecy connects directly to cloud data platforms such as Databricks, Snowflake, and BigQuery, allowing organizations to prepare, analyze, and govern data at enterprise scale. The platform combines AI-generated data pipelines with visual workflow interfaces, making complex data transformations easier to understand and manage. Users can automate data preparation, perform advanced analysis, create visualizations, and deploy production-ready workflows while maintaining governance and transparency.Starting Price: $150/user/month -
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IBM Db2
IBM
IBM Db2 is a family of data management products, including the Db2 relational database. The products feature AI-powered capabilities to help you modernize the management of both structured and unstructured data across on-premises and multicloud environments. By helping to make your data simple and accessible, the Db2 family positions your business to pursue the value of AI. Most of the Db2 family is available on the IBM Cloud Pak® for Data platform, either as an add-on or an included data source service, making virtually all of your data available across hybrid or multicloud environments to fuel your AI applications. Easily converge your transactional data stores and rapidly derive insights through universal, intelligent querying of data across disparate sources. Cut costs with the multimodel capability that eliminates the need for data replication and migration. Enhance agility by running Db2 on any cloud vendor. -
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Numbers Station
Numbers Station
Accelerating insights, eliminating barriers for data analysts. Intelligent data stack automation, get insights from your data 10x faster with AI. Pioneered at the Stanford AI lab and now available to your enterprise, intelligence for the modern data stack has arrived. Use natural language to get value from your messy, complex, and siloed data in minutes. Tell your data your desired output, and immediately generate code for execution. Customizable automation of complex data tasks that are specific to your organization and not captured by templated solutions. Empower anyone to securely automate data-intensive workflows on the modern data stack, free data engineers from an endless backlog of requests. Arrive at insights in minutes, not months. Uniquely designed for you, tuned for your organization’s needs. Integrated with upstream and downstream tools, Snowflake, Databricks, Redshift, BigQuery, and more coming, built on dbt. -
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Presto
Presto Foundation
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. For data engineers who struggle with managing multiple query languages and interfaces to siloed databases and storage, Presto is the fast and reliable engine that provides one simple ANSI SQL interface for all your data analytics and your open lakehouse. Different engines for different workloads means you will have to re-platform down the road. With Presto, you get 1 familar ANSI SQL language and 1 engine for your data analytics so you don't need to graduate to another lakehouse engine. Presto can be used for interactive and batch workloads, small and large amounts of data, and scales from a few to thousands of users. Presto gives you one simple ANSI SQL interface for all of your data in various siloed data systems, helping you join your data ecosystem together. -
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Querona
YouNeedIT
We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems. If you have ever experienced a lack of data you needed, time to consuming report generation or long queue to your BI expert, consider Querona. Querona uses a built-in Big Data engine to handle growing data volumes. Repeatable queries can be cached or calculated in advance. Optimization needs less effort as Querona automatically suggests query improvements. Querona empowers business analysts and data scientists by putting self-service in their hands. They can easily discover and prototype data models, add new data sources, experiment with query optimization and dig in raw data. Less IT is needed. Now users can get live data no matter where it is stored. If databases are too busy to be queried live, Querona will cache the data. -
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Apache Druid
Druid
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures. -
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TROCCO
primeNumber Inc
TROCCO is a fully managed modern data platform that enables users to integrate, transform, orchestrate, and manage their data from a single interface. It supports a wide range of connectors, including advertising platforms like Google Ads and Facebook Ads, cloud services such as AWS Cost Explorer and Google Analytics 4, various databases like MySQL and PostgreSQL, and data warehouses including Amazon Redshift and Google BigQuery. The platform offers features like Managed ETL, which allows for bulk importing of data sources and centralized ETL configuration management, eliminating the need to manually create ETL configurations individually. Additionally, TROCCO provides a data catalog that automatically retrieves metadata from data analysis infrastructure, generating a comprehensive catalog to promote data utilization. Users can also define workflows to create a series of tasks, setting the order and combination to streamline data processing. -
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Mozart Data
Mozart Data
Mozart Data is the all-in-one modern data platform that makes it easy to consolidate, organize, and analyze data. Start making data-driven decisions by setting up a modern data stack in an hour - no engineering required. -
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Dremio
Dremio
Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable. -
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Y42
Datos-Intelligence GmbH
Y42 is the first fully managed Modern DataOps Cloud. It is purpose-built to help companies easily design production-ready data pipelines on top of their Google BigQuery or Snowflake cloud data warehouse. Y42 provides native integration of best-of-breed open-source data tools, comprehensive data governance, and better collaboration for data teams. With Y42, organizations enjoy increased accessibility to data and can make data-driven decisions quickly and efficiently. -
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FeatureByte
FeatureByte
FeatureByte is your AI data scientist streamlining the entire lifecycle so that what once took months now happens in hours. Deployed natively on Databricks, Snowflake, BigQuery, or Spark, it automates feature engineering, ideation, cataloging, custom UDFs (including transformer support), evaluation, selection, historical backfill, deployment, and serving (online or batch), all within a unified platform. FeatureByte’s GenAI‑inspired agents, data, domain, MLOps, and data science agents interactively guide teams through data acquisition, quality, feature generation, model creation, deployment orchestration, and continued monitoring. FeatureByte’s SDK and intuitive UI enable automated and semi‑automated feature ideation, customizable pipelines, cataloging, lineage tracking, approval flows, RBAC, alerts, and version control, empowering teams to build, refine, document, and serve features rapidly and reliably. -
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Google Ads Data Hub
Google
Tailor your marketing measurement approach to your unique business needs. Ads Data Hub enables customized analysis that aligns with your specific business objectives while respecting user privacy and upholding Google’s high standards of data security. With Ads Data Hub, you can upload your first-party data into BigQuery and join it with Google event-level ad campaign data. Combining your data with Google event data can unlock insights, improve advertising efficiency, help you achieve data-driven business goals, and yield more effective campaign optimization. Results from Ads Data Hub are aggregated over a group of users, which allows Google to provide more complete data and still maintain end-user privacy. Ads Data Hub is built in a privacy-safe way, and its functionality differs significantly from other data warehousing solutions. Even experts with experience using other clean rooms and data warehousing solutions may need to learn how to operate effectively in Ads Data Hub. -
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Tabular
Tabular
Tabular is an open table store from the creators of Apache Iceberg. Connect multiple computing engines and frameworks. Decrease query time and storage costs by up to 50%. Centralize enforcement of data access (RBAC) policies. Connect any query engine or framework, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python. Smart compaction, clustering, and other automated data services reduce storage costs and query times by up to 50%. Unify data access at the database or table. RBAC controls are simple to manage, consistently enforced, and easy to audit. Centralize your security down to the table. Tabular is easy to use plus it features high-powered ingestion, performance, and RBAC under the hood. Tabular gives you the flexibility to work with multiple “best of breed” compute engines based on their strengths. Assign privileges at the data warehouse database, table, or column level.Starting Price: $100 per month -
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Alteryx
Alteryx
Step into a new era of analytics with the Alteryx AI Platform. Empower your organization with automated data preparation, AI-powered analytics, and approachable machine learning — all with embedded governance and security. Welcome to the future of data-driven decisions for every user, every team, every step of the way. Empower your teams with an easy, intuitive user experience allowing everyone to create analytic solutions that improve productivity, efficiency, and the bottom line. Build an analytics culture with an end-to-end cloud analytics platform and transform data into insights with self-service data prep, machine learning, and AI-generated insights. Reduce risk and ensure your data is fully protected with the latest security standards and certifications. Connect to your data and applications with open API standards. -
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Gathr.ai
Gathr.ai
Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500Starting Price: $0.25/credit -
43
Tempo BigQuery Connector for Jira
Tempo Software
BigQuery Connector for Jira is a no-code integration that loads Jira data into Google BigQuery for large-scale analysis and reporting. Export any Jira data – standard fields, custom fields, history, and agile metrics – plus data from across the Tempo suite (Timesheets, Capacity Planner, Financial Manager) and other Marketplace apps. Calculated fields like Time in Status and Time at Assignee come built in. Filter with basic options or JQL, schedule automatic refreshes, and keep your BigQuery datasets consistently up to date – no coding required. Granular permissions and sharing settings keep data access aligned to user roles. Built for enterprise, government, and education teams running analytics on a cloud data warehouse. BigQuery Connector for Jira is part of Tempo's Strategic Portfolio Management (SPM) suite, alongside Tempo Structure PPM, Timesheets, Capacity Planner, and Financial Manager.Starting Price: $10/month/user -
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Dataform
Google
Dataform enables data analysts and data engineers to develop and operationalize scalable data transformation pipelines in BigQuery using only SQL from a single, unified environment. Its open source core language lets teams define table schemas, configure dependencies, add column descriptions, and set up data quality assertions within a shared code repository while applying software development best practices, version control, environments, testing, and documentation. A fully managed, serverless orchestration layer automatically handles workflow dependencies, tracks lineage, and executes SQL pipelines on demand or via schedules in Cloud Composer, Workflows, BigQuery Studio, or third-party services. In the browser-based development interface, users get real-time error feedback, visualize dependency graphs, connect to GitHub or GitLab for commits and code reviews, and launch production-grade pipelines in minutes without leaving BigQuery Studio.Starting Price: Free -
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REGRESSwise
iQspeaks Limited
REGRESSwise is an enterprise-grade regression testing platform built natively for Google BigQuery. Developed by iQspeaks Limited, it enables data engineering and QA teams to automate validation of high-scale data pipelines with fast and reliable before-and-after comparison testing. The platform supports schema validation, row-level comparison, and aggregate-level validation to identify data inconsistencies, schema drift, and transformation issues before production deployment. REGRESSwise integrates directly into existing CI/CD workflows and complements dbt testing by validating output data rather than transformation logic. Built for enterprise environments, REGRESSwise processes millions of data points efficiently while ensuring data integrity, auditability, and low BigQuery compute costs. The platform is ideal for organizations using GCP and BigQuery for analytics and large-scale data transformation workloads.Starting Price: $500 -
46
Conversionomics
Conversionomics
Set up all the automated connections you want, no per connection charges. Set up all the automated connections you want, no per-connection charges. Set up and scale your cloud data warehouse and processing operations – no tech expertise required. Improvise and ask the hard questions of your data – you’ve prepared it all with Conversionomics. It’s your data and you can do what you want with it – really. Conversionomics writes complex SQL for you to combine source data, lookups, and table relationships. Use preset Joins and common SQL or write your own SQL to customize your query and automate any action you could possibly want. Conversionomics is an efficient data aggregation tool that offers a simple user interface that makes it easy to quickly build data API sources. From those sources, you’ll be able to create impressive and interactive dashboards and reports using our templates or your favorite data visualization tools.Starting Price: $250 per month -
47
Google Cloud Data Fusion
Google
Open core, delivering hybrid and multi-cloud integration. Data Fusion is built using open source project CDAP, and this open core ensures data pipeline portability for users. CDAP’s broad integration with on-premises and public cloud platforms gives Cloud Data Fusion users the ability to break down silos and deliver insights that were previously inaccessible. Integrated with Google’s industry-leading big data tools. Data Fusion’s integration with Google Cloud simplifies data security and ensures data is immediately available for analysis. Whether you’re curating a data lake with Cloud Storage and Dataproc, moving data into BigQuery for data warehousing, or transforming data to land it in a relational store like Cloud Spanner, Cloud Data Fusion’s integration makes development and iteration fast and easy. -
48
Google Cloud Datalab
Google
An easy-to-use interactive tool for data exploration, analysis, visualization, and machine learning. Cloud Datalab is a powerful interactive tool created to explore, analyze, transform, and visualize data and build machine learning models on Google Cloud Platform. It runs on Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks. Cloud Datalab is built on Jupyter (formerly IPython), which boasts a thriving ecosystem of modules and a robust knowledge base. Cloud Datalab enables analysis of your data on BigQuery, AI Platform, Compute Engine, and Cloud Storage using Python, SQL, and JavaScript (for BigQuery user-defined functions). Whether you're analyzing megabytes or terabytes, Cloud Datalab has you covered. Query terabytes of data in BigQuery, run local analysis on sampled data, and run training jobs on terabytes of data in AI Platform seamlessly. -
49
Google Cloud Datastream
Google
Serverless and easy-to-use change data capture and replication service. Access to streaming data from MySQL, PostgreSQL, AlloyDB, SQL Server, and Oracle databases. Near real-time analytics in BigQuery. Easy-to-use setup with built-in secure connectivity for faster time-to-value. A serverless platform that automatically scales, with no resources to provision or manage. Log-based mechanism to reduce the load and potential disruption on source databases. Synchronize data across heterogeneous databases, storage systems, and applications reliably, with low latency, while minimizing impact on source performance. Get up and running fast with a serverless and easy-to-use service that seamlessly scales up or down, and has no infrastructure to manage. Connect and integrate data across your organization with the best of Google Cloud services like BigQuery, Spanner, Dataflow, and Data Fusion. -
50
Brewit
Brewit
Make data-driven decisions 10x faster with self-service analytics. Integrate with your databases and data warehouses all-in-one place (Postgres, MySQL, Snowflake, BigQuery, and more). Brewit can write SQL queries and create recommended charts based on your data questions. It also helps you drill down on the analysis. Chat with your database, visualize insights, & perform analysis. Ensure answer accuracy and consistency with a built-in data catalog. An automated semantic layer that ensures Brewit answers with correct business logic. Easily manage your data catalog & data dictionary. Building a beautiful report is as easy as writing a doc. Data without a story is useless. Our Notion-style notebook editor allows you to create reports & dashboards easily, turning raw data into actionable insights. All organized data products are usable by anyone who has a data question, regardless of their technical skills.
