Best Data Platform & Integration Tools

Data Governance Software for Snowflake, Databricks & Modern Data Platforms. Control data at the source with Expanso's Hybrid Data Management platform.

Provision and mask test data for development and QA teams automatically

Monitor data quality, track pipeline performance, and manage enterprise workloads across hybrid environments

Manage website cookie banners and user consent to comply with privacy regulations

Extract, harmonize, and deliver marketing data across hundreds of sources to your data warehouse

Reconcile conflicting business records across different apps into verified data for artificial intelligence

Replicate and sync data across hundreds of sources to warehouses and databases

Build and run secure cloud data infrastructure for regulated organizations

Transform raw unstructured data into traceable knowledge graphs for enterprise AI reasoning

Govern company data and monitor machine learning models across enterprise environments

Cache remote cloud storage data close to compute clusters to accelerate machine learning workflows

Automate data preparation, analysis workflows, and reporting without writing code

Reduce Google BigQuery compute costs through automated SQL query rewriting and routing

Unify fragmented customer records across different channels into single profiles for marketing campaigns

Helps automate and enhance GA4 data management and reporting.

Monitor data pipelines automatically to detect missing records, anomalies, and schema changes

Store and process huge datasets across distributed computer clusters with automatic failure handling

Process massive batch and streaming data across distributed clusters of computers

Store, index, and search multimodal data using vector and graph database technologies

Replicate database changes directly into your cloud data warehouse in real time

Unify hospitality customer data and send targeted marketing campaigns

Provides enterprise for business management and operations

Run and manage Apache Airflow data pipelines reliably

Monitor data quality, track lineage, and govern business datasets for enterprise analytics

Connect enterprise data catalogs, business definitions, and lineage directly to your AI agents

Connect business intelligence tools and AI agents to cloud data through unified semantic models

Run Apache Kafka directly on cloud object storage without local disks

Define, review, and validate product analytics event tracking before code hits production

Store, query, and analyze connected data relationships for knowledge graphs and fraud detection

Build automated data pipelines and integrate diverse data sources visually without code

Store object data and back up computer files with S3-compatible cloud storage

Enrich credit card transactions with item-level receipt data for commerce and banking

Automate data pipelines to ingest, clean, and validate business records without writing code

Monitor data quality, trace lineage, and identify sensitive information across your enterprise data pipelines

Collect first-party conversion data and route server-side events to marketing channels

Build and manage secure data infrastructure across hybrid enterprise environments

Share and deliver data products across multiple clouds, data warehouses, and AI agents

Run Python, Pandas, and SQL across distributed CPUs and GPUs without code changes

Identify unknown brick-and-mortar shoppers from point-of-sale data to expand reachable customer audiences

Analyze restaurant customer data and get targeted campaign recommendations to drive sales

Capture first-party customer data and receipt information from offline retail sales

Connect financial data to AI models using standardized metrics and granular access controls

Chat2DB is an AI-powered SQL client that transforms natural language into SQL queries. Supports MySQL, Redis, MongoDB, and enhances database management with Text2SQL and BI features.

Manage chromatography methods, column inventories, and analytical laboratory test data in one place

Store, ingest, analyze, and deploy data pipelines and predictive models in one environment

Standardize and govern marketing campaign taxonomy and content metadata across channels

Fast open-source column-oriented database management system that allows generating analytical data reports in real-time using SQL queries

Sync cloud infrastructure and SaaS data into your SQL database

Discover, document, and query company data assets using natural language search

Monitor data quality, track data lineage, and resolve data pipeline incidents automatically

Build, automate, and govern cloud data warehouse pipelines

Unify industrial asset data and run automated workflows across enterprise facilities

Govern enterprise data, catalog assets, and audit models

Stream data in real time across systems using Apache Kafka

Discover, classify, and clean up unstructured enterprise data to reduce storage and security risks

Validate and secure complex data pipelines for artificial intelligence and connected hardware systems

Query and analyze high-volume streaming data in real time using standard SQL

Collect, route, transform, and search telemetry data across diverse security and IT systems

Ingest, transform, and monitor external financial data pipelines into cloud warehouses

Structure geospatial and time-series sensor data for real-time analytics and spatial applications

Data orchestrator platform that helps you build, schedule, and monitor reliable data pipelines - fast, flexible, and built for teams.

Build, schedule, and track asset-based data pipelines across your entire tech stack

Clean, match, and deduplicate enterprise records across multiple databases

A tool for seamless data integration and management.

Catalog and govern enterprise data assets and map their relationships across departments

Query structured, semi-structured, and vector data using an open-source cloud data warehouse

Store, process, and analyze massive datasets while building artificial intelligence models and workflows

Automate database migrations and test data quality across your pipelines and warehouses

Build, orchestrate, and observe declarative data pipelines directly inside your cloud warehouse

Clean, deduplicate, and verify contact data inside Salesforce without manual rule building

Catalog data assets and track lineage across your organization

Store unstructured vector data and build retrieval-augmented generation applications at scale

Transform, test, and document data in your cloud warehouse using modular SQL code

Build and execute real-time streaming data pipelines using SQL, Java, and Python

Access, test, and integrate external data sources through centralized automated data pipelines

Connect, govern, and query distributed enterprise data sources without moving or copying data

Collaborate on version-controlled relational databases using familiar Git and SQL workflows

Discover Dragonfly - the most performant in-memory data store, engineered for extreme throughput at scale.

Query and manage enterprise data lakehouses directly for analytics and AI workloads

Import, validate, and clean spreadsheet data directly inside your web applications

Generate metadata, score data quality, and redact sensitive records inside your cloud infrastructure

Store, query, and analyze multidimensional scientific data cubes in cloud storage

Build and monitor automated data pipelines across enterprise systems

Integrate and migrate operational data from acquired companies into centralized databases

Design conceptual data models and maintain business glossaries collaboratively in your browser

Prepare, clean, and combine complex data sets using visual workflows on desktop or cloud

Track and preserve digital asset provenance and object histories across blockchains

Govern sensitive enterprise data and enforce privacy policies across AI models in real time

Automate data ingestion, validation, and delivery across alternative investment operations and systems

Process, filter, and route telemetry data at the source before sending it downstream

Keep complex SQL query results up to date continuously as your data changes

Access real-time and historical stock market fundamentals and SEC filings via API

Turn financial transaction data into targeted marketing offers and personalized banking recommendations

Run fast analytical SQL queries over large datasets using open table formats

Automatically move and replicate data from various sources into warehouses and lakes

Migrate and distribute object data across multiple cloud storage providers

Track healthcare marketing performance and conversion attribution while maintaining patient data privacy compliance

Collect and sync first-party customer data to marketing channels for online stores

Collect, clean, and export your marketing data to reporting destinations and warehouses

Drive team adoption and measure financial return from your existing enterprise AI tools

Manage relational data using graph queries, integrated authentication, and built-in vector search

Back up, archive, and replicate enterprise SaaS data into your own cloud environment

Validate, test, and document pipeline data to prevent bad records downstream

Build audiences and orchestrate customer journeys directly from your data warehouse

Share, distribute, and monetize enterprise data externally with automated access controls

Build 10x faster with the first fully native Graph-Vector Database combining the power of graph and vector types natively in Rust to build RAG and AI applications easily

Access real-time and historical multi-chain blockchain data for enterprise applications

Replicate and load data from multiple sources into your warehouse with automated pipelines

Model, transform, and deliver industrial machine data to cloud applications without writing code

Sync customer data from cloud data warehouses directly to marketing and business tools

Provide data infrastructure, hybrid cloud, and AI solutions for businesses

Honeydew's semantic layer for AI and BI helps data teams create a shared source of truth for business logic on their Snowflake data

Analyze reader habits and screen academic submissions to grow publisher revenue

Store and retrieve AI agent memory using a graph database on object storage

Store, ingest, and query massive streaming log datasets using cloud object storage

Manage and deliver structured digital content across websites and apps using GraphQL APIs

Control and audit data access permissions for humans and automated agents across enterprise databases

Migrate data between business apps and CRMs without handling spreadsheets

Connect marketing data sources and analyze cross-channel performance

Build and run real-time event streaming data pipelines from edge to cloud

Store, query, and analyze high-resolution time series data in real time

Connect, govern, and manage enterprise data across multiple clouds and applications

Connect customer datasets across different companies without sharing or exposing sensitive underlying records

Clean, standardize, and deduplicate customer data across multiple CRM systems

Store large volumes of data onchain with built-in verification and flexible retention durations

Provides distributed caching for high-traffic applications with ultra-low latency

Run fast interactive business intelligence queries on massive Hadoop datasets

Collect event data into your warehouse

Package fragmented enterprise business data into reusable data products for operational and analytical systems

Teach AI data agents how to query your data warehouse accurately

Protect and link sensitive data across workflows without exposing identities or raw records

Connect financial data across multiple systems and automate reporting for audit compliance

Connect language models and automated workflows to verified financial and business databases

Use declarative language to build simpler, faster, scalable and flexible workflows

Organize, structure, and syndicate chemical and industrial product data across internal business systems

Manage customer loyalty programs and automate personalized marketing campaigns across retail channels

Host, version, and share geospatial datasets with automated APIs and natural language queries

Connect construction databases to data warehouses and artificial intelligence assistants for unified analytics

Create a unified semantic layer across enterprise data for faster analytics queries

Manage and version data lakes with Git-like branching, merging, and rollback capabilities

An open-source, serverless vector database for AI that allows you to store, manage, and query embeddings, metadata, and full-text search directly on disk or object storage.

Consolidate developer touchpoints and community interactions into unified profiles across platforms

Monitor and validate enterprise data pipelines continuously with automated anomaly detection

Automate customer integrations with AI. Connect

Build, run, and monitor automated data pipelines using Python and SQL

Package and license AI agent interaction logs to research labs for revenue

Manticore Search is an easy-to-use open source fast database for search. Elasticsearch alternative, vector search, SQL interface, full-text search capabilities

Extract, transform, and load data into cloud warehouses using visual pipelines and automated agents

Query connected data and power AI reasoning with an in-memory graph database

Catalog data assets and manage metadata standards across your entire organization

Monitor data quality and catch pipeline issues before they affect downstream analytics dashboards

Build and manage relational databases without writing complex code

Store and manage high-speed object data for AI

Store, query, and process document data across multiple clouds and local environments

Run fast SQL analytics in the cloud using DuckDB without managing infrastructure

Sync business APIs to your databases and data warehouses in real time

Centralize scattered business data into a managed cloud warehouse with automated transformation pipelines

Connect customer data across apps and build targeted marketing audiences

Migrate legacy ERP systems to modern cloud environments and rebuild business integrations

Normalize, enrich, and share data across external ad networks and cloud platforms

Create serverless Postgres databases that automatically scale compute and storage

Connect AI agents to enterprise data systems through governed model context protocol servers

Turn enterprise datasets into decentralized autonomous data products ready for AI models and analytics

Build real-time streaming data applications directly from event sources like Apache Kafka

Standardize and enrich financial transaction data across any data source in milliseconds

Scan websites to audit privacy compliance, analytics tracking tags, and digital accessibility standards

Import, clean, map, and validate messy spreadsheet data into your databases

Store, visualize, and share complex underwater geophysical data directly in your web browser

Store, process, and manage large-scale transactional and analytical data across distributed systems

Run agentic AI and complex analytical queries directly on petabyte-scale enterprise data

Sync customer data from your warehouse directly to your business tools

Run fast data lakehouse ingestion and ETL pipelines inside your cloud account

Clean, transform, and validate messy spreadsheet and file data across systems

Build the best CSV Excel Import Experience for SaaS in 10 Minutes. Onboard customers data with a hassle-free data importer in your app.

Clean, enrich, and route go-to-market data across business databases without code

Resolve audience identities across channels and sell advertising inventory directly to buying agents

Track end-to-end data lineage and automate enterprise metadata management across complex legacy systems

Catalog, govern, and trace data lineage across your enterprise systems

Store linked data and execute semantic reasoning rules in real time

Connect complex enterprise data sources to coordinate operational workflows and automated decisions

Consolidate distributed file storage into a single hybrid cloud system with real-time sync

Connect scattered databases, SaaS tools, and APIs into a unified queryable source

Connect fragmented public safety data to coordinate emergency responses and investigations in real time

Replicate, backup, and sync ServiceNow data across external databases and business applications

Store and search vector embeddings at scale for retrieval-augmented generation applications

Host, scale, and manage relational databases with branching and automated failover

Collect and route data feeding autonomous AI agents

Sync data between databases, cloud applications, APIs, and spreadsheets in both directions

Replicate data from over fifteen hundred business applications directly into cloud data warehouses

Build marketing reports and manage campaigns using AI

Store, query, and manage structured application data using open-source relational database technology

Extract and combine structured enterprise records and document data for analytics workflows

Orchestrate data pipelines, machine learning workflows, and background jobs using plain Python code

Sync live application data directly to and from your customers' data warehouses

Query relational databases and lakehouses as unified graphs without running ETL pipelines

Store, search, and manage high-dimensional vector embeddings for machine learning applications

Validate and monitor data quality automatically before it reaches downstream analytics and AI workflows

Connect multiple bank data providers through one API

Store, manage, and access unstructured file and object data across hybrid cloud environments

Stream real-time data and manage access controls for autonomous artificial intelligence agents

Clean, deduplicate, and route customer contact data

Process streaming data in real time using familiar SQL queries and PostgreSQL connections

Index and query real-time data to build responsive analytical applications

Connect digital audience data across devices without cookies

Collect, unify, and route customer event data directly into data warehouses and business apps

Manage data catalogs, track lineage, monitor quality metrics, and govern business definitions automatically

Integrate, cleanse, and manage structured and unstructured enterprise data across varied sources

The best operating system for modern biotech. Join 100+ biotechs that use Scispot to collect, clean, and activate their data - and supercharge R&D.

Clean and standardise complex spreadsheet data automatically for business workflows

Catalog, monitor, and govern enterprise data assets with automated metadata and lineage tracking

Catalog data assets and track column-level lineage across databases and dashboards

Manage and run scientific data analysis pipelines

Edit and analyze records across business apps using an embedded spreadsheet interface

Streamline your asset management with Shelf's intuitive, open-source platform. Track, manage, and optimize your equipment effortlessly. Start your free trial today!

Detect data pipeline issues, track end-to-end lineage, and resolve root causes across data stacks

Run transactional and analytical database workloads together in real time

Verify addresses, validate emails, and track mailings for postal discounts

Store, process, and analyze enterprise data while running machine learning models across multiple clouds

Collect and deliver real-time user behavioral data to your data warehouse and AI systems

Find, monitor, and fix data quality issues across your databases and pipelines

Map and visualize data flows to trace compliance and changes across complex systems

Connect, validate, and query architecture and engineering 3D model data across applications

Synchronize operational data both ways across enterprise systems, databases, and warehouses in real time

Automate civic data workflows and connect legacy public agency systems to modern analytics

Host server-side Google Tag Manager containers and manage marketing analytics tracking

Query distributed data across multiple databases and cloud lakes without moving or copying files

Automates data governance and observability

Stream real-time data into lakehouses and serve live context to applications and agents

Build and deploy streaming data pipelines across multicloud environments without writing code

Stream and integrate database events into cloud warehouses in real time

Sync Stripe payment data directly to your data warehouse automatically

Preserve searchable records and operational knowledge before decommissioning legacy systems

Pull marketing data directly into spreadsheets, dashboards, and AI assistants for reporting

License company operational data securely to AI labs to generate new revenue streams

Store documents, graphs, vectors, and relational records in a single database engine

Unify revenue data across ad servers and finance systems into central analytics storage

Unify, synchronize, and clean master data across business applications in real time

Clean, connect, and activate automotive dealership customer data across CRM and DMS systems

Connect convenience store sales, fuel, loyalty, and inventory data into a unified database

TDengine is an AI-powered data historian built on a high-performance time-series database with an industrial data management layer and AI copilot.

Collect, unify, and route customer data across web, mobile, and cloud applications in real time

Integrate and share sensitive enterprise data securely across strict security boundaries

Monitor data pipelines and detect anomalies across data lakes continuously

Monitor data pipelines and detect anomalies across data lakes and warehouses

Manage enterprise datasets, run analytics, and deploy autonomous agents across hybrid cloud environments

Connect wearable and health data to your app

Automate real-time decisions from streaming data

Bring AI-native applications to life with less hallucination, data leakage, and vendor lock-in

Turn existing enterprise data into reusable data products for analytics and AI applications

A fully managed, auto-scaling database designed for dynamic workloads. Get started with a generous free tier.

Store, query, and scale transactional records, vector embeddings, and real-time analytics across distributed clusters

Store and query massive time-series data using PostgreSQL at petabyte scale

Leading AI-powered graph database. Uncover hidden relationships, run real-time analytics at scale, and power fraud detection, customer ...

Process real-time streaming and historical data with SQL queries in a single binary

Validate industrial IoT and sensor data to prevent errors in analytics and operations

Generate realistic, privacy-compliant synthetic data for development, testing, and AI model training.

Fuse fragmented multi-source data to generate real-time operational understanding for defense missions

Manage real-time data governance, privacy compliance, and AI agent permissions centrally

Store and search vector and full-text data on object storage

An edge-first database built on libSQL (SQLite fork) designed for low-latency AI applications and millions of individual database instances.

Transform complex documents, tables, and scans into structured data for machine learning models

Run serverless Redis, vector databases, and messaging

Access and share customer energy data directly from utilities through standardized APIs

Store, manage, and process massive datasets across distributed environments for artificial intelligence workloads

Manage data access permissions and enforce compliance policies across enterprise databases

Observes your query traffic, learns semantic definitions, and enforces them through pull requests. Stop debugging metric drift. Start shipping contracts.

Collaborate on sensitive datasets and share verified answers without exposing the raw data

Archive and tier exabyte-scale unstructured data across tape and cloud

Sync, clean, and organize customer data across sales, marketing, and finance applications

Access IBM Z mainframe data directly from cloud environments in real time

Validate and enrich point-of-interest data for maps, apps, and analytics

Protect digital content and automate data licensing for artificial intelligence training

Store and deliver data rapidly to GPUs for high-performance machine learning workloads

Ingest, standardize, and deliver real-time weather and sensor data directly to your applications

Connect marketing and business data to analytics tools, spreadsheets, and artificial intelligence chats

Discover spreadsheet risks and track data lineage across critical enterprise files

Branch Postgres databases instantly for pull requests, automated tests, and coding agents

Accelerate Apache Spark queries and cut cloud compute costs without rewriting code

Build, monitor, and maintain data pipelines without managing complex underlying infrastructure

Connect, clean, and standardize fragmented farm and supply chain data for better decision-making

Stream clinical trial patient data from electronic health records to electronic data capture systems

Run distributed PostgreSQL databases across multiple clouds with built-in high availability and vector search

Migrate enterprise legacy data and track data lineage across financial systems

Discover, catalog, and govern reports and dashboards across multiple analytics applications in one place

Store and search billions of high-dimensional vectors for enterprise artificial intelligence applications

Resolve duplicate customer entities and build golden records across your data warehouses

Unify and enrich business customer data to improve marketing and sales targeting