Best Data Management Software for SQL - Page 5
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Compare the Top Data Management Software that integrates with SQL as of November 2025 - Page 5
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This a list of Data Management software that integrates with SQL. Use the filters on the left to add additional filters for products that have integrations with SQL. View the products that work with SQL in the table below.
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1
Feast
Tecton
Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution. -
2
Zepl
Zepl
Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github. -
3
AI2sql
AI2sql.io
With AI2sql, engineers and non-engineers can easily write efficient, error-free SQL queries without knowing SQL. All you need to do is enter a few keywords about your data - AI2sql automatically builds an optimized SQL query for your data resulting in extremely fast performance. We wanted to share some exciting numbers with you about how many people have tried out AI2sql, and what they've been able to accomplish with it. To get the best results with AI2sql, it is important to clearly define your goals and use the tool's customization options, test and verify the generated SQL. You can also try changing the prompts or input used to generate the SQL statements to see if this results in more accurate or efficient queries. -
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Savant
Savant
Automate data access from data platforms and apps, explore, prep, blend, analyze and deliver bot-driven insights where and when needed. From data access to delivery of insights, create workflows in minutes to automate every step of analytics from data access to delivery of insights. Put an end to shadow analytics. Create and collaborate with all stakeholders in one platform. Audit and govern workflows. The single platform for supply-chain, HR, sales & marketing analytics integrating Fivetran, Snowflake, DBT, Workday, Pendo, Marketo, PowerBI. No code. No limits. Savant's no-code platform lets you stitch, transform and analyze data using the same functions you're comfortable using in Excel and SQL. All steps are automatable, so you can focus on analysis, not tedious manual work. -
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AI Query
AI Query
Use simple English and let AI do the heavy lifting for you. With AI Query anyone can create efficient SQL queries, without even knowing a thing about it. Once your database schema is ready, you can easily generate SQL queries with simple text prompts. Let the AI do the work for you.Starting Price: $10 per month -
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Quadratic
Quadratic
Quadratic enables your team to work together on data analysis to deliver faster results. You already know how to use a spreadsheet, but you’ve never had this much power. Quadratic speaks Formulas and Python (SQL & JavaScript coming soon). Use the language you and your team already know. Single-line formulas are hard to read. In Quadratic you can expand your recipes to as many lines as you need. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. The last line of code is returned to the spreadsheet. Raw values, 1/2D arrays, and Pandas DataFrames are supported by default. Pull or fetch data from an external API, and it updates automatically in Quadratic's cells. Navigate with ease, zoom out for the big picture, and zoom in to focus on the details. Arrange and navigate your data how it makes sense in your head, not how a tool forces you to do it. -
7
SQLGPT
SQLGPT
Import your database schema and easily generate customized queries. Using ChatGPT to write and understand your SQL requests. To export only the schema (i.e., the database structure) in a MySQL database, you can use the mysqldump command with the no-data option. Our platform is designed to connect to your existing database and provide you with tools to manage and analyze your data. We understand that the security and privacy of your data are of utmost importance, and we take all necessary precautions to ensure that your data remains secure and confidential. When you use our platform, your data remains under your control and stored in your own database. We do not collect, store, or share your data with any third-party entities. Select the database you want to export. You can download the exported file to your computer or save it to the selected location. You can save it to your computer or send it to a remote server. -
8
LlamaIndex
LlamaIndex
LlamaIndex is a “data framework” to help you build LLM apps. Connect semi-structured data from API's like Slack, Salesforce, Notion, etc. LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. LlamaIndex provides the key tools to augment your LLM applications with data. Connect your existing data sources and data formats (API's, PDF's, documents, SQL, etc.) to use with a large language model application. Store and index your data for different use cases. Integrate with downstream vector store and database providers. LlamaIndex provides a query interface that accepts any input prompt over your data and returns a knowledge-augmented response. Connect unstructured sources such as documents, raw text files, PDF's, videos, images, etc. Easily integrate structured data sources from Excel, SQL, etc. Provides ways to structure your data (indices, graphs) so that this data can be easily used with LLMs. -
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Polars
Polars
Knowing of data wrangling habits, Polars exposes a complete Python API, including the full set of features to manipulate DataFrames using an expression language that will empower you to create readable and performant code. Polars is written in Rust, uncompromising in its choices to provide a feature-complete DataFrame API to the Rust ecosystem. Use it as a DataFrame library or as a query engine backend for your data models. -
10
Baidu Palo
Baidu AI Cloud
Palo helps enterprises to create the PB-level MPP architecture data warehouse service within several minutes and import the massive data from RDS, BOS, and BMR. Thus, Palo can perform the multi-dimensional analytics of big data. Palo is compatible with mainstream BI tools. Data analysts can analyze and display the data visually and gain insights quickly to assist decision-making. It has the industry-leading MPP query engine, with column storage, intelligent index,and vector execution functions. It can also provide in-library analytics, window functions, and other advanced analytics functions. You can create a materialized view and change the table structure without the suspension of service. It supports flexible and efficient data recovery. -
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Serverless computing is ideal for systems with unpredictable loads. Storage scaling, query execution, and backup layers are fully automated. The compatibility of the service API in serverless mode allows you to use the AWS SDKs for Java, JavaScript, Node.js, .NET, PHP, Python, and Ruby. YDB is hosted in three availability zones, ensuring availability even if a node or availability zone goes offline. If equipment or a data center fails, the system automatically recovers and continues working. YDB is tailored to meet high-performance requirements and can process hundreds of thousands of transactions per second with low latency. The system was designed to handle hundreds of petabytes of data.
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Arroyo
Arroyo
Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes. -
13
definity
definity
Monitor and control everything your data pipelines do with zero code changes. Monitor data and pipelines in motion to proactively prevent downtime and quickly root cause issues. Optimize pipeline runs and job performance to save costs and keep SLAs. Accelerate code deployments and platform upgrades while maintaining reliability and performance. Data & performance checks in line with pipeline runs. Checks on input data, before pipelines even run. Automatic preemption of runs. definity takes away the effort to build deep end-to-end coverage, so you are protected at every step, across every dimension. definity shifts observability to post-production to achieve ubiquity, increase coverage, and reduce manual effort. definity agents automatically run with every pipeline, with zero footprints. Unified view of data, pipelines, infra, lineage, and code for every data asset. Detect in run-time and avoid async checks. Auto-preempt runs, even on inputs. -
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Decentriq
Decentriq
Privacy-minded organizations work with Decentriq. With the latest advancements in encryption and privacy-enhancing technologies such as synthetic data, differential privacy, and confidential computing, your data stays under your control at all times. End-to-end encryption keeps your data private to all other parties. Decentriq cannot see or access your data. Remote attestation gives you verification that your data is encrypted and only approved analyses are running. Built-in partnership with market-leading hardware and infrastructure providers. Designed to handle even advanced AI and machine learning models, the platform keeps your data inaccessible no matter the challenge. With processing speeds approaching typical cloud levels, you don’t have to sacrifice scalability for excellent data protection. Our growing network of data connectors supports more streamlined workflows across leading data platforms. -
15
Actian Ingres
Actian
Ultra-reliable SQL-standard transactional database with X100 operational analytics. Actian Ingres has long been known as an ultra-reliable enterprise transactional database. Today Actian Ingres is a hybrid transactional/analytical processing database with record-breaking performance. Ingres supports both row-based and columnar storage formats using its ultra-reliable enterprise transactional database, and Vector’s X100 analytics engine. This combination allows organizations to perform transaction processing and operational analytics easily and efficiently within a single database. The most trusted and time-tested transactional database with a low total cost of ownership, 24/7 global support, and industry-leading customer satisfaction. It has a proven track record, with thousands of enterprises running billions of transactions over decades of deployment, upgrades, and migrations. -
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Chat2DB
Chat2DB
Save time by working with data. Connect to all your data sources, and instantly generate optimal SQL for fast lightning information. If you don't know SQL well, you can get instant information without writing SQL. Generate high-performance SQL for your complicated queries using natural language, as well as correcting errors and getting AI suggestions to optimize the performance of SQL queries. Developers can write complex SQL queries quickly and accurately with the help of the AI SQL editor, saving time and improving development efficiency. Just enter the names of the tables and columns, and we will automatically configure the type, password, and comment, saving you 90% of the time. Imports and exports data in multiple formats (CSV, XLSX, XLS, SQL) to facilitate exchange, backup, and migration. Transfers data between different databases or through cloud services, as a backup and recovery solution that guarantees the minimum loss of data and downtime during migrations.Starting Price: $7 per month -
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Oceanbase
Oceanbase
OceanBase eliminates the complexity of traditional sharding databases, enabling you to effortlessly scale your database to meet ever-growing workloads, whether horizontally, vertically, or even at the tenant level. This facilitates on-the-fly scaling and linear performance growth without downtime or necessitating changes to applications in high-concurrency scenarios, ensuring quicker and more reliable responses to performance-intensive critical workloads. Empower mission-critical workloads and performance-intensive applications across both OLTP and OLAP scenarios, all while maintaining full compatibility with MySQL. 100% ACID Compliance, natively supports distributed transactions with multi-replica strong synchronization built upon Paxos protocols. Experience ultimate query performance that your mission-critical and time-sensitive workloads can depend on. This effectively eliminates downtime, and ensures your mission-critical workload remains always available. -
18
Microsoft Intelligent Data Platform
Microsoft
The Microsoft Intelligent Data Platform is an integrated data and AI platform designed to help organizations adapt rapidly, add intelligence to applications, and generate predictive insights. It unifies databases, analytics, and governance, enabling businesses to invest more time in creating value rather than managing their data estate. The platform offers seamless data integration and real-time business intelligence, facilitating powerful decision-making and innovation. By breaking down data silos, it allows organizations to extract real-time insights with the necessary data governance to operate safely. The platform's capabilities include accelerating innovation, improving productivity through automation and AI, and enhancing agility by anticipating changes and improving decision-making. It also provides comprehensive security across the data lifecycle, helping protect hybrid and multi-cloud environments. -
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ibi Open Data Hub for Mainframe
Cloud Software Group
ibi Open Data Hub for Mainframe provides real-time access to mainframe data, enabling seamless integration with various business intelligence tools. By allowing data to remain on the mainframe, it ensures compliance with security protocols and regulatory standards. The platform reduces the need for custom SQL queries, enhancing productivity and facilitating prompt, informed decision-making. Utilizing zIIP specialty engines, it offers cost-effective data access by offloading workloads from general-purpose processors. This solution empowers organizations to respond swiftly to market trends and customer demands by providing comprehensive, up-to-date business data. Reduce the time to gain access to data by eliminating the need for custom SQL queries so you can retrieve and analyze information faster to ensure faster decision-making. Access the data from the mainframe in real time to develop insights that let you make informed decisions promptly. -
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Nextdata
Nextdata
Nextdata is a data mesh operating system designed to decentralize data management, enabling organizations to create, share, and manage data products across various data stacks and formats. By encapsulating data, metadata, code, and policies into portable containers, it simplifies the data supply chain, ensuring data is useful, safe, and discoverable. Automated policy enforcement is embedded as code, continuously evaluating and maintaining data quality and compliance. The system integrates seamlessly with existing data infrastructures, allowing configuration and provisioning of data products as needed. It supports processing data from any source in any format, facilitating analytics, machine learning, and generative AI applications. Nextdata automatically generates and synchronizes real-time metadata and semantic models throughout the data product's lifecycle, enhancing discoverability and usability. -
21
SQLNotebook
TimeStored
SQL Notebooks allow developers to write Markdown combined with SQL to produce live HTML5 reports. They offer a lightning-fast, modern HTML5 interface where data sources are queried in real time. Users can create beautiful, live-updating SQL notebooks, easily source control the code, and take static snapshots to share with colleagues who don't have database access. SQL Notebooks are available in both QStudio Version 4, a desktop SQL client based on editing markdown files locally, and Pulse Version 3, which serves as a shared team server accessible via a web address. To help users get started, a showcase of example notebooks has been created in collaboration with leading community members; these examples are snapshotted versions with static data, and the source markdown and most of the data to recreate them are available on GitHub. -
22
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. -
23
SQream
SQream
SQream is a GPU-accelerated data analytics platform that enables organizations to process large, complex datasets with unprecedented speed and efficiency. By leveraging NVIDIA's GPU technology, SQream executes intricate SQL queries on vast datasets rapidly, transforming hours-long processes into minutes. It offers dynamic scalability, allowing businesses to seamlessly scale their data operations in line with growth, without disrupting analytics workflows. SQream's architecture supports deployments that provide flexibility to meet diverse infrastructure needs. Designed for industries such as telecom, manufacturing, finance, advertising, and retail, SQream empowers data teams to gain deep insights, foster data democratization, and drive innovation, all while significantly reducing costs. -
24
Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. Built on Amazon DataZone, it integrates various AWS analytics and AI/ML services, such as Amazon EMR, AWS Glue, and Amazon Bedrock, into a single platform. Users can discover, access, and process data from various sources like Amazon S3 and Redshift, and develop generative AI applications. With tools for model development, governance, MLOps, and AI customization, SageMaker Unified Studio provides an efficient, secure, and collaborative environment for data teams.
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25
SDF
SDF
SDF is a developer platform for data that enhances SQL comprehension across organizations, enabling data teams to unlock the full potential of their data. It provides a transformation layer to streamline query writing and management, an analytical database engine for local execution, and an accelerator for improved transformation processes. SDF also offers proactive quality and governance features, including reports, contracts, and impact analysis, to ensure data integrity and compliance. By representing business logic as code, SDF facilitates the classification and management of data types, enhancing the clarity and maintainability of data models. It integrates seamlessly with existing data workflows, supporting various SQL dialects and cloud environments, and is designed to scale with the growing needs of data teams. SDF's open-core architecture, built on Apache DataFusion, allows for customization and extension, fostering a collaborative ecosystem for data development. -
26
Borneo
Borneo
Borneo is a real-time data security and privacy observability platform designed to help organizations discover, remediate, and govern data risks while ensuring privacy and compliance. It enables users to discover where health data, financial data, and PII are stored across unstructured data, SaaS apps, and public cloud environments. Borneo's risk correlation engine identifies data that violates security frameworks and privacy regulations, prompting immediate action. It offers automatic remediation through data masking, access changes, and encryption, and continuously monitors changes across the data landscape to maintain compliance and eliminate regulatory risk. Built by security practitioners from Uber, Facebook, and Yahoo, Borneo is crafted to handle data at scale. It features a powerful connector framework to integrate across diverse data landscapes, supports flexible and modular deployment, and ensures that data never leaves the user's cloud environment. -
27
SchemaFlow
SchemaFlow
SchemaFlow is a powerful tool designed to enhance AI-powered development by providing real-time access to your PostgreSQL database schema through the Model Context Protocol (MCP). It allows developers to connect their databases, visualize schema structures with interactive diagrams, and export schemas in various formats such as JSON, Markdown, SQL, and Mermaid. With native MCP support via Server-Sent Events (SSE), SchemaFlow enables seamless integration with AI-Integrated Development Environments (AI-IDEs) like Cursor, Windsurf, and VS Code, ensuring that AI assistants have up-to-date schema information for accurate code generation. It offers secure token-based authentication for MCP connections, automatic schema synchronization to keep AI assistants informed of any changes, and a schema browser for easy navigation of tables and relationships. -
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Glitter
Glitter
Glitter Protocol is a blockchain-based data platform built to assist developers in storing, managing, and elevating the world’s data in a Web3-native way. It offers multi-language SDKs (including via SQL) and a role-based access control system for secure dataset writing and collaboration. The platform includes an indexing engine with both traditional database and full-text search capabilities, enabling efficient data discovery and retrieval. Glitter enables data sharing and monetization through token-economics; data contributors are incentivized to provide valuable datasets, and developers can access a marketplace-style “datamap” to locate data assets. It supports the migration of existing Web2 applications and data into the Web3 ecosystem, aiming to organize and decentralize unstructured data, make it more accessible and usable, and foster collaboration across the community. -
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Crux
Crux
Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics. -
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Channel
Channel AI
Ask any data question, in plain English. Connect your database, ask a question, get an answer. Get the answers you need without knowing SQL. Self serve your data insights, finally. Query in plain english. No matter how complex your warehouse, Channel learns how to get the answers you need from just plain English. Beautiful visualization. Channel automatically generates beautiful visualizations for your data, and picks the right chart type based on your preferences. Self service, for real. Channel is designed to be used by anyone, from analysts to product managers. No more waiting for the data you need. Answer the questions you should be asking. Channel surfaces the insights you didn't know you needed, by analyzing your warehouse ahead of time. Combine your knowledge. Channel learns from every questions it's ever asked, and prompts you to ask the questions that really matter. Shared definitions. Keep track of how important terms are defined across your organization.
