Best Big Data Platforms for DataGrip
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Compare the Top Big Data Platforms that integrate with DataGrip as of October 2025
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This a list of Big Data platforms that integrate with DataGrip. Use the filters on the left to add additional filters for products that have integrations with DataGrip. View the products that work with DataGrip in the table below.
What are Big Data Platforms for DataGrip?
Big data platforms are systems that provide the infrastructure and tools needed to store, manage, process, and analyze large volumes of structured and unstructured data. These platforms typically offer scalable storage solutions, high-performance computing capabilities, and advanced analytics tools to help organizations extract insights from massive datasets. Big data platforms often support technologies such as distributed computing, machine learning, and real-time data processing, allowing businesses to leverage their data for decision-making, predictive analytics, and process optimization. By using these platforms, organizations can handle complex datasets efficiently, uncover hidden patterns, and drive data-driven innovation. Compare and read user reviews of the best Big Data platforms for DataGrip currently available using the table below. This list is updated regularly.
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1
Google Cloud BigQuery
Google
BigQuery is designed to handle and analyze big data, making it an ideal tool for businesses working with massive datasets. Whether you are processing gigabytes or petabytes, BigQuery scales automatically and delivers high-performance queries, making it highly efficient. With BigQuery, organizations can analyze data at unprecedented speed, helping them stay ahead in fast-moving industries. New customers can leverage the $300 in free credits to explore BigQuery's big data capabilities, gaining practical experience in managing and analyzing large volumes of information. The platform’s serverless architecture ensures that users never have to worry about scaling issues, making big data management simpler than ever.Starting Price: Free ($300 in free credits) -
2
Google Cloud Platform
Google
Google Cloud Platform excels in managing and analyzing big data through tools like BigQuery, a serverless data warehouse for fast querying and analysis. GCP also offers services such as Dataflow, Dataproc, and Pub/Sub, which allow businesses to efficiently process and analyze large datasets. With the added benefit of $300 in free credits for new customers to run, test, and deploy workloads, organizations can start exploring big data solutions without the financial commitment, accelerating their data-driven insights and innovations. The platform’s highly scalable architecture enables companies to process terabytes to petabytes of data quickly and at a fraction of the cost of traditional data solutions. GCP's big data solutions are designed to integrate well with machine learning tools, creating a comprehensive environment for data scientists and analysts to gain valuable insights.Starting Price: Free ($300 in free credits) -
3
MongoDB
MongoDB
MongoDB is a general purpose, document-based, distributed database built for modern application developers and for the cloud era. No database is more productive to use. Ship and iterate 3–5x faster with our flexible document data model and a unified query interface for any use case. Whether it’s your first customer or 20 million users around the world, meet your performance SLAs in any environment. Easily ensure high availability, protect data integrity, and meet the security and compliance standards for your mission-critical workloads. An integrated suite of cloud database services that allow you to address a wide variety of use cases, from transactional to analytical, from search to data visualizations. Launch secure mobile apps with native, edge-to-cloud sync and automatic conflict resolution. Run MongoDB anywhere, from your laptop to your data center.Starting Price: Free -
4
Microsoft Azure
Microsoft
Microsoft's Azure is a cloud computing platform that allows for rapid and secure application development, testing and management. Azure. Invent with purpose. Turn ideas into solutions with more than 100 services to build, deploy, and manage applications—in the cloud, on-premises, and at the edge—using the tools and frameworks of your choice. Continuous innovation from Microsoft supports your development today, and your product visions for tomorrow. With a commitment to open source, and support for all languages and frameworks, build how you want, and deploy where you want to. On-premises, in the cloud, and at the edge—we’ll meet you where you are. Integrate and manage your environments with services designed for hybrid cloud. Get security from the ground up, backed by a team of experts, and proactive compliance trusted by enterprises, governments, and startups. The cloud you can trust, with the numbers to prove it. -
5
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 compute/month -
6
OpenText Analytics Database is a high-performance, scalable analytics platform that enables organizations to analyze massive data sets quickly and cost-effectively. It supports real-time analytics and in-database machine learning to deliver actionable business insights. The platform can be deployed flexibly across hybrid, multi-cloud, and on-premises environments to optimize infrastructure and reduce total cost of ownership. Its massively parallel processing (MPP) architecture handles complex queries efficiently, regardless of data size. OpenText Analytics Database also features compatibility with data lakehouse architectures, supporting formats like Parquet and ORC. With built-in machine learning and broad language support, it empowers users from SQL experts to Python developers to derive predictive insights.
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7
Exasol
Exasol
With an in-memory, columnar database and MPP architecture, you can query billions of rows in seconds. Queries are distributed across all nodes in a cluster, providing linear scalability for more users and advanced analytics. MPP, in-memory, and columnar storage add up to the fastest database built for data analytics. With SaaS, cloud, on premises and hybrid deployment options you can analyze data wherever it lives. Automatic query tuning reduces maintenance and overhead. Seamless integrations and performance efficiency gets you more power at a fraction of normal infrastructure costs. Smart, in-memory query processing allowed this social networking company to boost performance, processing 10B data sets a year. A single data repository and speed engine to accelerate critical analytics, delivering improved patient outcome and bottom line.
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