Alternatives to Dataform
Compare Dataform alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Dataform in 2026. Compare features, ratings, user reviews, pricing, and more from Dataform competitors and alternatives in order to make an informed decision for your business.
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1
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
2
dbt
dbt Labs
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence. -
3
DbVisualizer
DbVisualizer
DbVisualizer is a universal database client for developers, DBAs, analysts, and data engineers working with relational and NoSQL databases. It provides a graphical interface for database development, SQL querying, data exploration, and database admin. The tool includes a powerful SQL editor with intelligent autocomplete, visual query builders, variables, and query execution tools. Customize window layouts, key bindings, and UI themes, mark scripts or database objects as favorites, and configure security settings to meet organizational requirements. Ask questions, explain errors, and analyze code with the built-in AI Assistant. Use the built-in Git integration to manage your SQL scripts and collaboration. DbVisualizer connects to many popular databases through JDBC drivers, including MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, SQLite, Cassandra, and BigQuery. It runs on Windows, macOS, and Linux. Nearly 7 million downloads and Pro users in 150 countries. -
4
Kubit
Kubit
Your data, your insights—no third-party ownership or black-box analytics. Kubit is the leading Customer Journey Analytics platform for enterprises, enabling self-service insights, rapid decisions, and full transparency—without engineering dependencies or vendor lock-in. Unlike traditional tools, Kubit eliminates data silos, letting teams analyze customer behavior directly from Snowflake, BigQuery, or Databricks—no ETL or forced extraction needed. With built-in funnel, path, retention, and cohort analysis, Kubit empowers product teams with fast, exploratory analytics to detect anomalies, surface trends, and drive engagement—without compromise. Enterprises like Paramount, TelevisaUnivision, and Miro trust Kubit for its agility, reliability, and customer-first approach. Learn more at kubit.ai. -
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Managed Service for Apache Airflow is a fully managed workflow orchestration platform from Google Cloud built on the open-source Apache Airflow project. It allows users to author, schedule, and monitor data pipelines using Python-based workflows known as DAGs. The platform eliminates the need to manage infrastructure, enabling teams to focus on building and running pipelines. It integrates seamlessly with Google Cloud services such as BigQuery, Dataflow, and Managed Service for Apache Spark. It also supports hybrid and multi-cloud environments, allowing workflows to span across different systems. Users benefit from built-in monitoring, logging, and troubleshooting tools for reliability. The service is designed to simplify complex data workflows, including ETL, MLOps, and automation tasks. Overall, it provides a scalable and flexible solution for orchestrating modern data pipelines.Starting Price: $0.074 per vCPU hour
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6
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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Alooma
Google
Alooma enables data teams to have visibility and control. It brings data from your various data silos together into BigQuery, all in real time. Set up and flow data in minutes or customize, enrich, and transform data on the stream before it even hits the data warehouse. Never lose an event. Alooma's built in safety nets ensure easy error handling without pausing your pipeline. Any number of data sources, from low to high volume, Alooma’s infrastructure scales to your needs. -
8
Orchestra
Orchestra
Orchestra is a Unified Control Plane for Data and AI Operations, designed to help data teams build, deploy, and monitor workflows with ease. It offers a declarative framework that combines code and GUI, allowing users to implement workflows 10x faster and reduce maintenance time by 50%. With real-time metadata aggregation, Orchestra provides full-stack data observability, enabling proactive alerting and rapid recovery from pipeline failures. It integrates seamlessly with tools like dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and more, ensuring compatibility with existing data stacks. Orchestra's modular architecture supports AWS, Azure, and GCP, making it a versatile solution for enterprises and scale-ups aiming to streamline their data operations and build trust in their AI initiatives. -
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Datazoom
Datazoom
Improving the experience, efficiency, and profitability of streaming video requires data. Datazoom enables video publishers to better operate distributed architectures through centralizing, standardizing, and integrating data in real-time to create a more powerful data pipeline and improve observability, adaptability, and optimization solutions. Datazoom is a video data platform that continually gathers data from endpoints, like a CDN or a video player, through an ecosystem of collectors. Once the data is gathered, it is normalized using standardized data definitions. This data is then sent through available connectors to analytics platforms like Google BigQuery, Google Analytics, and Splunk and can be visualized in tools such as Looker and Superset. Datazoom is your key to a more effective and efficient data pipeline. Get the data you need in real-time. Don’t wait for your data when you need to resolve an issue immediately. -
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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. -
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CData Sync
CData Software
CData Sync is a universal data pipeline that delivers automated continuous replication between hundreds of SaaS applications & cloud data sources and any major database or data warehouse, on-premise or in the cloud. Replicate data from hundreds of cloud data sources to popular database destinations, such as SQL Server, Redshift, S3, Snowflake, BigQuery, and more. Configuring replication is easy: login, select the data tables to replicate, and select a replication interval. Done. CData Sync extracts data iteratively, causing minimal impact on operational systems by only querying and updating data that has been added or changed since the last update. CData Sync offers the utmost flexibility across full and partial replication scenarios and ensures that critical data is stored safely in your database of choice. Download a 30-day free trial of the Sync application or request more information at www.cdata.com/sync -
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Tokern
Tokern
Open source data governance suite for databases and data lakes. Tokern is a simple to use toolkit to collect, organize and analyze data lake's metadata. Run as a command-line app for quick tasks. Run as a service for continuous collection of metadata. Analyze lineage, access control and PII datasets using reporting dashboards or programmatically in Jupyter notebooks. Tokern is an open source data governance suite for databases and data lakes. Improve ROI of your data, comply with regulations like HIPAA, CCPA and GDPR and protect critical data from insider threats with confidence. Centralized metadata management of users, datasets and jobs. Powers other data governance features. Track Column Level Data Lineage for Snowflake, AWS Redshift and BigQuery. Build lineage from query history or ETL scripts. Explore lineage using interactive graphs or programmatically using APIs or SDKs. -
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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. -
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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 -
15
Logflare
Logflare
Never get surprised by a logging bill again, collect for years, query in seconds. Costs escalates quickly with typical log management solutions. To setup long term analytics on events you need to archive to a CSV and setup another data pipeline to ingest events into a custom tailored data warehouse. With Logflare and BigQuery there is no setup for long term analytics. You can ingest immediately, query in seconds and store data for years. Use our Cloudflare app and catch every request to your web service no matter what. Our Cloudflare App worker doesn't modify your request, it simply pulls the request/response data and logs to Logflare asynchronously after passing your request through. Want to monitor your Elixir app? Our library adds minimal overhead. We batch logs and use BERT binary serialization to keep payload size and serialization load low. When you sign in with your Google account, we give you access to your underlying BigQuery table.Starting Price: $5 per month -
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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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Clarisights
Granular Insights
The decision platform for growth. Realtime, interactive and contextual reporting for high performance marketing teams. Spreadsheets and BI Tools were not built for today. Poor context and static reporting coupled with high dependency on IT and Analyst teams cripples performance in an increasingly complex marketing mix. Clarisights, the Platform You Deserve today. You don’t need IT teams to maintain your data or analysts to answer your questions. Effortlessly consolidate your data and find insights in realtime - Take full control of your marketing decisions. Integrate - Announcing the Death of Data Silos. No pixels or SDKs, no data pipelines to build. Add more context with realtime data from native integrations. Blazing Fast Setup Few clicks to sign-up, less than a week to better reports Native Integrations Joined data across channels at deepest granularity. Custom Data Sources, CRMs, BigQuery, Redshift and more - Get all the data you need. -
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PeerDB
PeerDB
If Postgres is at the core of your business and is a major source of data, PeerDB provides a fast, simple, and cost-effective way to replicate data from Postgres to data warehouses, queues, and storage. Designed to run at any scale, and tailored for data stores. PeerDB uses replication messages from the Postgres replication slot to replay the schema messages. Alerts for slot growth and connections. Native support for Postgres toast columns and large JSONB columns for IoT. Optimized query design to reduce warehouse costs; particularly useful for Snowflake and BigQuery. Support for partitioned tables via both publish. Blazing fast and consistent initial load by transaction snapshotting and CTID scans. High-availability, in-place upgrades, autoscaling, advance logs, metrics and monitoring dashboards, burstable instance types, and suitable for dev environments.Starting Price: $250 per month -
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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. -
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nao
nao
nao is an AI-powered data IDE designed specifically for data teams, combining a code editor with native integration to your data warehouse so you can write, test, and maintain data-centric code with full context. It supports warehouses such as Postgres, Snowflake, BigQuery, Databricks, DuckDB, Motherduck, Athena, and Redshift. Once connected, nao replaces a traditional data-warehouse console by offering schema-aware SQL auto-completion, data previews, SQL worksheets, and the ability to switch easily between multiple warehouses. The core of nao is its AI agent, which has full awareness of your actual data schema, tables, columns, metadata, and your codebase or data-stack context. It can generate SQL queries or full data-transformation models (e.g., for dbt workflows), refactor code, add or update documentation, run data-quality checks and data-diff tests, and even surface insights or run exploratory analytics, all while respecting data structure and quality constraints.Starting Price: $30 per month -
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Agile Data Engine
Agile Data Engine
Agile Data Engine is a comprehensive DataOps platform designed to streamline the development, deployment, and operation of cloud-based data warehouses. It integrates data modeling, transformations, continuous deployment, workflow orchestration, monitoring, and API connectivity within a single SaaS solution. The platform's metadata-driven approach automates SQL code generation and data load workflows, enhancing productivity and agility in data operations. Supporting multiple cloud database platforms, including Snowflake, Databricks SQL, Amazon Redshift, Microsoft Fabric (Warehouse), Azure Synapse SQL, Azure SQL Database, and Google BigQuery, Agile Data Engine offers flexibility in cloud environments. Its modular data product framework and out-of-the-box CI/CD pipelines facilitate seamless integration and continuous delivery, enabling data teams to adapt swiftly to changing business requirements. The platform also provides insights and statistics on data platform performance. -
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StreamScape
StreamScape
Make use of Reactive Programming on the back-end without the need for specialized languages or cumbersome frameworks. Triggers, Actors and Event Collections make it easy to build data pipelines and work with data streams using simple SQL-like syntax, shielding users from the complexities of distributed system development. Extensible Data Modeling is a key feature that supports rich semantics and schema definition for representing real-world things. On-the-fly validation and data shaping rules support a variey of formats like XML and JSON, allowing you to easily describe and evolve your schema, keeping pace with changing business requirements. If you can describe it, we can query it. Know SQL and Javascript? Then you already know how to use the data engine. Whatever the format, a powerful query language lets you instantly test logic expressions and functions, speeding up development and simplifying deployment for unmatched data agility. -
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GlassFlow
GlassFlow
GlassFlow is a serverless, event-driven data pipeline platform designed for Python developers. It enables users to build real-time data pipelines without the need for complex infrastructure like Kafka or Flink. By writing Python functions, developers can define data transformations, and GlassFlow manages the underlying infrastructure, offering auto-scaling, low latency, and optimal data retention. The platform supports integration with various data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, through its Python SDK and managed connectors. GlassFlow provides a low-code interface for quick pipeline setup, allowing users to create and deploy pipelines within minutes. It also offers features such as serverless function execution, real-time API connections, and alerting and reprocessing capabilities. The platform is designed to simplify the creation and management of event-driven data pipelines, making it accessible for Python developers.Starting Price: $350 per month -
24
Upsolver
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries. -
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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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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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Text2SQL.AI
Text2SQL.AI
Generate SQL with AI in seconds. Turn your thoughts into complex SQL queries using natural language. Text2SQL.AI uses theOpenAI GPT-3 Codexmodel which can translate English prompts to SQL queries, and SQL queries to English text. It is currently the most advanced Natural Language Processing tool available, and this is the exact same model which used by Github Copilot. The app currently supports: SQL generation from English textual instructions. Supports SELECT, UPDATE, DELETE queries, CREATE and ALTER TABLE requests, constraints, window functions, and literally everything! SQL query explanation to plain English Your custom database schema (tables, fields, types) connection (with history) SQL dialects for MySQL, PostgreSQL, Snowflake, BigQuery, MS SQL Server... If you have any other feature request, please let us know. -
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QuerySurge
RTTS
QuerySurge is the enterprise-grade data quality platform that continuously automates the validation of data across your entire ecosystem ‐ from data warehouses and big data lakes to BI reports and enterprise applications. With AI-powered test creation, a scalable architecture, and seamless CI/CD integration, QuerySurge consistently ensures data integrity at every stage of the pipeline: accelerating delivery, reducing risk, and enabling confident decision-making. Use Cases - Data Warehouse & ETL Testing - Big Data Testing - DevOps for Data / DataOps / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise App/ERP Testing QuerySurge Features - Data Validation: enterprise-grade platform - AI: Automatically create data validation tests - BI Report Testing: Fully automated, no-code approach - DevOps for Data (DataOps): API w/60+ calls & Swagger docs, integrate continuous testing into your CI/CD pipelines - Data Connectors: For 200+ platforms -
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Qlik Compose
Qlik
Qlik Compose for Data Warehouses provides a modern approach by automating and optimizing data warehouse creation and operation. Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, all whilst leveraging best practices and proven design patterns. Qlik Compose for Data Warehouses dramatically reduces the time, cost and risk of BI projects, whether on-premises or in the cloud. Qlik Compose for Data Lakes automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments. -
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Pylar
Pylar
Pylar is a secure data-access layer that sits between AI agents and your databases, enabling agents to safely interact with structured data without giving them direct database access. It connects to one or more data sources (like BigQuery, Snowflake, PostgreSQL, business apps such as HubSpot or Google Sheets). Pylar can create governed SQL views using its built-in SQL IDE; those views define exactly which tables, columns, and rows agents are allowed to access. It lets you build “MCP tools” (either by writing natural-language prompts or manual configuration) that wrap SQL queries into standardized, safe operations. Agents can access data through a single MCP endpoint, compatible with multiple agent builders like custom AI assistants, no-code automation tools, or integrations (e.g. Zapier, n8n, LangGraph, VS Code, etc.).Starting Price: $20 per month -
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Managed Service for Apache Spark is a Google Cloud solution that simplifies running Apache Spark workloads with either serverless execution or fully managed clusters. It allows users to process large-scale data without needing to manage infrastructure, reducing operational complexity. The platform features Lightning Engine, which accelerates Spark performance by up to 4.9 times compared to open-source Spark. It supports data engineering, data science, and machine learning workflows at scale. Integration with Gemini enables AI-powered development, including automated code generation and troubleshooting. The service works seamlessly with open data formats like Apache Iceberg and integrates with tools like BigQuery and Knowledge Catalog. It offers flexible deployment options to suit different workloads and use cases. Overall, it provides a faster, smarter, and more efficient way to run Spark workloads in the cloud.
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Ingestro
Ingestro
Ingestro is an enterprise-grade, AI-powered data import solution designed to help software companies clean, validate, and onboard customer data faster. It supports uploads from a wide variety of formats—including CSV, Excel, XML, JSON, and even PDFs—while automatically mapping, cleaning, and restructuring the data to match each company’s schema. With its Data Importer SDK and Data Pipelines, Ingestro enables teams to offer a seamless self-serve import experience without building in-house tools. The platform improves scalability by automating recurring data onboarding tasks, reducing dependency on developers, and accelerating customer time-to-value. Companies rely on Ingestro to process billions of records securely thanks to features like ISO 27001 certification, GDPR compliance, and optional self-hosting. By transforming tedious data imports into smooth, AI-enhanced workflows, Ingestro helps product, engineering, and customer success teams reclaim valuable time. -
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Astrato
Astrato Analytics
Astrato Analytics is a warehouse-native business intelligence platform that allows organizations to build, embed, and share interactive dashboards and data applications directly on cloud data warehouses. It integrates with major platforms such as Snowflake, BigQuery, Databricks, ClickHouse, Supabase, Amazon Redshift, PostgreSQL, and Dremio. The platform uses a zero-copy architecture, enabling real-time data access without the need for data extraction or duplication. This approach ensures that dashboards and reports always reflect the most up-to-date information. Astrato connects through a live-query engine, allowing seamless interaction with source data. It eliminates the complexity of managing data pipelines or cached datasets. Security is enhanced by inheriting policies like row-level access and data masking directly from the warehouse. Overall, it simplifies analytics while maintaining strong governance and real-time insights.Starting Price: $12/month/user -
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Mitzu
Mitzu.io
Mitzu is an agentic analytics platform that runs your analytics directly on your data warehouse — no data copying, no reverse ETL, no SQL required. Its AI analytics agent answers business questions autonomously: it maps your schema, writes and executes queries on Snowflake, BigQuery, Redshift, Databricks, or ClickHouse, and returns explainable results with full SQL visibility. Teams get instant access to funnels, retention, cohorts, user journeys, and revenue metrics. Mitzu also proactively monitors KPIs and sends anomaly alerts via Slack or email. Available as SaaS, BYOC, or fully self-hosted. Free trial available at mitzu.ioStarting Price: $35 per month -
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Datavolo
Datavolo
Capture all your unstructured data for all your LLM needs. Datavolo replaces single-use, point-to-point code with fast, flexible, reusable pipelines, freeing you to focus on what matters most, doing incredible work. Datavolo is the dataflow infrastructure that gives you a competitive edge. Get fast, unencumbered access to all of your data, including the unstructured files that LLMs rely on, and power up your generative AI. Get pipelines that grow with you, in minutes, not days, without custom coding. Instantly configure from any source to any destination at any time. Trust your data because lineage is built into every pipeline. Make single-use pipelines and expensive configurations a thing of the past. Harness your unstructured data and unleash AI innovation with Datavolo, powered by Apache NiFi and built specifically for unstructured data. Our founders have spent a lifetime helping organizations make the most of their data.Starting Price: $36,000 per year -
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Gemini Enterprise Agent Platform Notebooks provide a unified environment for data science workflows, combining the flexibility of Colab Enterprise with the power of Agent Platform Workbench. These notebooks enable users to explore data, build models, and deploy solutions without switching between multiple tools. With seamless integration into Google Cloud services like BigQuery and Apache Spark, users can analyze large datasets directly within the notebook interface. The platform supports rapid prototyping and model development by offering scalable compute resources and AI-powered coding assistance. It allows teams to move from experimentation to production efficiently using end-to-end workflows. Fully managed infrastructure ensures scalability, cost optimization, and minimal operational overhead. Enterprise-grade security features such as single sign-on and access controls provide a safe environment for development.Starting Price: $10 per GB
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Catalog
Coalesce
Catalog from Coalesce (formerly CastorDoc) is a data catalog designed for mass adoption across the whole company. Have an overview of all your data environment. Search for data instantly thanks to our powerful search engine. Onboard to a new data infrastructure and access data in a breeze. Go beyond your traditional data catalog. Modern data teams now have numerous data sources, build one truth. With its delightful and automated documentation experience, Catalog makes it dead simple to trust data. Column-level, cross-system data lineage in minutes. Get a bird’s eye view of your data pipelines to build trust in your data. Troubleshoot data issues, perform impact analyses, comply with GDPR in one tool. Optimize performance, cost, compliance, and security for your data. Keep your data stack healthy with our automated infrastructure monitoring system.Starting Price: $699 per month -
38
Vanna.AI
Vanna.AI
Vanna.AI is an AI-powered platform designed to help users interact with their databases by asking questions in natural language. It enables both beginners and experts to quickly obtain insights from large datasets without needing to write complex SQL queries. Users simply ask a question, and Vanna automatically identifies the relevant tables and columns to retrieve the data needed. The platform integrates with popular databases like Snowflake, BigQuery, and Postgres and supports various front-end implementations such as Jupyter Notebooks, Slackbots, and web apps. Vanna's open source model allows for secure, self-hosted deployments and can continuously improve its performance as it learns from the user's interactions. It is ideal for businesses looking to democratize access to data insights and simplify the query process.Starting Price: $25 per month -
39
Chalk
Chalk
Powerful data engineering workflows, without the infrastructure headaches. Complex streaming, scheduling, and data backfill pipelines, are all defined in simple, composable Python. Make ETL a thing of the past, fetch all of your data in real-time, no matter how complex. Incorporate deep learning and LLMs into decisions alongside structured business data. Make better predictions with fresher data, don’t pay vendors to pre-fetch data you don’t use, and query data just in time for online predictions. Experiment in Jupyter, then deploy to production. Prevent train-serve skew and create new data workflows in milliseconds. Instantly monitor all of your data workflows in real-time; track usage, and data quality effortlessly. Know everything you computed and data replay anything. Integrate with the tools you already use and deploy to your own infrastructure. Decide and enforce withdrawal limits with custom hold times.Starting Price: Free -
40
Adele
Adastra
Adele is an intuitive platform designed to simplify the migration of data pipelines from any legacy system to a target platform. It empowers users with full control over the functional migration process, while its intelligent mapping capabilities offer valuable insights. By reverse-engineering data pipelines, Adele creates data lineage mappings and extracts metadata, enhancing visibility and understanding of data flows. -
41
Pantomath
Pantomath
Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage. -
42
Nextflow
Seqera Labs
Data-driven computational pipelines. Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages. Its fluent DSL simplifies the implementation and deployment of complex parallel and reactive workflows on clouds and clusters. Nextflow is built around the idea that Linux is the lingua franca of data science. Nextflow allows you to write a computational pipeline by making it simpler to put together many different tasks. You may reuse your existing scripts and tools and you don't need to learn a new language or API to start using it. Nextflow supports Docker and Singularity containers technology. This, along with the integration of the GitHub code-sharing platform, allows you to write self-contained pipelines, manage versions, and rapidly reproduce any former configuration. Nextflow provides an abstraction layer between your pipeline's logic and the execution layer.Starting Price: Free -
43
Google VPC Service Controls
Google
VPC Service Controls. Managed networking functionality for your Google Cloud resources. New customers get $300 in free credits to spend on Google Cloud during the first 90 days. All customers get free usage (up to monthly limits) of select products, including BigQuery and Compute Engine. Mitigate exfiltration risks by isolating multi-tenant services. Ensure sensitive data can only be accessed from authorized networks. Restrict resource access to allowed IP addresses, identities, and trusted client devices. Control which Google Cloud services are accessible from a VPC network. Enforce a security perimeter with VPC Service Controls to isolate resources of multi-tenant Google Cloud services—reducing the risk of data exfiltration or data breach. Configure private communication between cloud resources from VPC networks spanning cloud and on-premises hybrid deployments. Take advantage of fully managed tools like Cloud Storage, Bigtable, and BigQuery. -
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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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Oarkflow
Oarkflow
Automate your business pipeline with our flow builder. Use operations that matters to you. Bring your own service providers for email, sms and http services. Use our advanced query builder to query and analyze csv with any field numbers and rows. We store the csv files you've uploaded on our platform in a secured vault and account activity logs. We don't store any data records you request for processing.Starting Price: $0.0005 per task -
46
Google Cloud Data Studio
Google
Google Cloud Data Studio is a web-based business intelligence and data visualization tool that transforms raw data into interactive, fully customizable reports and dashboards that are easy to read, share, and explore. It allows users to connect to hundreds of data sources, including Google products like Analytics, Ads, BigQuery, spreadsheets, and many third-party platforms, unifying data into a single view without coding. It features an intuitive drag-and-drop editor with customizable charts, tables, and visual elements, enabling users to build dynamic dashboards that update in real time as data changes. With a wide library of templates, users can quickly create professional reports or design their own layouts to match specific business needs. Looker Studio emphasizes collaboration and accessibility, allowing reports to be shared with individuals, teams, or publicly, with real-time co-editing and the ability to embed dashboards into websites or internal tools.Starting Price: Free -
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AWS Data Pipeline
Amazon
AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR. AWS Data Pipeline helps you easily create complex data processing workloads that are fault tolerant, repeatable, and highly available. You don’t have to worry about ensuring resource availability, managing inter-task dependencies, retrying transient failures or timeouts in individual tasks, or creating a failure notification system. AWS Data Pipeline also allows you to move and process data that was previously locked up in on-premises data silos.Starting Price: $1 per month -
48
Unravel
Unravel Data
Unravel is an AI-native data observability platform designed to help modern enterprises detect, resolve, and prevent data issues at scale. It uses intelligent, automated agents that work alongside data teams to surface insights, guide decisions, and reduce operational toil. Unravel brings data observability and FinOps together, enabling organizations to improve performance, ensure reliability, and optimize cloud data spending. The platform provides end-to-end visibility across pipelines, workloads, and infrastructure. With agent-driven actionability™, Unravel can take action on behalf of teams, integrate directly with existing tools, or recommend next-best actions. It supports major data platforms including Databricks, Snowflake, and Google Cloud BigQuery. By combining automation with human control, Unravel transforms data observability into a collaborative, always-on partner. -
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Google Cloud Pub/Sub
Google
Google Cloud Pub/Sub. Scalable, in-order message delivery with pull and push modes. Auto-scaling and auto-provisioning with support from zero to hundreds of GB/second. Independent quota and billing for publishers and subscribers. Global message routing to simplify multi-region systems. High availability made simple. Synchronous, cross-zone message replication and per-message receipt tracking ensure reliable delivery at any scale. No planning, auto-everything. Auto-scaling and auto-provisioning with no partitions eliminate planning and ensures workloads are production-ready from day one. Advanced features, built in. Filtering, dead-letter delivery, and exponential backoff without sacrificing scale help simplify your applications. A fast, reliable way to land small records at any volume, an entry point for real-time and batch pipelines feeding BigQuery, data lakes and operational databases. Use it with ETL/ELT pipelines in Dataflow. -
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Google Cloud Healthcare API
Google
The Google Cloud Healthcare API is a fully managed service that enables secure and scalable data exchange between healthcare applications and solutions. It supports industry-standard protocols and formats, including DICOM, FHIR, and HL7v2, allowing for the ingestion, storage, and analysis of healthcare data within the Google Cloud environment. By integrating with advanced analytics and machine learning tools such as BigQuery, AutoML, and Gemini Enterprise Agent Platform, the API empowers healthcare organizations to derive actionable insights and drive innovation in patient care and operational efficiency.
