Alternatives to Datus
Compare Datus alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Datus in 2026. Compare features, ratings, user reviews, pricing, and more from Datus competitors and alternatives in order to make an informed decision for your business.
-
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
DataBuck
FirstEigen
DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world. -
3
AnalyticsCreator
AnalyticsCreator
AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack. At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design. Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns. Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets. AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes. Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules. Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering. -
4
IBM Cognos Analytics acts as your trusted co-pilot for business with the aim of making you smarter, faster, and more confident in your data-driven decisions. IBM Cognos Analytics gives every user — whether data scientist, business analyst or non-IT specialist — more power to perform relevant analysis in a way that ties back to organizational objectives. It shortens each user’s journey from simple to sophisticated analytics, allowing them to harness data to explore the unknown, identify new relationships, get a deeper understanding of outcomes and challenge the status quo. Visualize, analyze and share actionable insights about your data with anyone in your organization with IBM Cognos Analytics.
-
5
Looker
Google
Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time. -
6
Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
7
Peekdata
Peekdata
Consume data from any database, organize it into consistent metrics, and use it with every app. Build your Data and Reporting APIs faster with automated SQL generation, query optimization, access control, consistent metrics definitions, and API design. It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for data engineers and application developers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review and configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling AP Ready-to-use Report Builder and JavaScript components for charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. And you will not have to make custom report queries anymore!Starting Price: $349 per month -
8
Fivetran
Fivetran
Fivetran is a leading data integration platform that centralizes an organization’s data from various sources to enable modern data infrastructure and drive innovation. It offers over 700 fully managed connectors to move data automatically, reliably, and securely from SaaS applications, databases, ERPs, and files to data warehouses and lakes. The platform supports real-time data syncs and scalable pipelines that fit evolving business needs. Trusted by global enterprises like Dropbox, JetBlue, and Pfizer, Fivetran helps accelerate analytics, AI workflows, and cloud migrations. It features robust security certifications including SOC 1 & 2, GDPR, HIPAA, and ISO 27001. Fivetran provides an easy-to-use, customizable platform that reduces engineering time and enables faster insights. -
9
Databricks
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
10
Stardog
Stardog Union
With ready access to the richest flexible semantic layer, explainable AI, and reusable data modeling, data engineers and scientists can be 95% more productive — create and expand semantic data models, understand any data interrelationship, and run federated queries to speed time to insight. Stardog offers the most advanced graph data virtualization and high-performance graph database — up to 57x better price/performance — to connect any data lakehouse, warehouse or enterprise data source without moving or copying data. Scale use cases and users at lower infrastructure cost. Stardog’s inference engine intelligently applies expert knowledge dynamically at query time to uncover hidden patterns or unexpected insights in relationships that enable better data-informed decisions and business outcomes.Starting Price: $0 -
11
Dosi
Datus
Dosi is a downloadable AI data analyst engine for data and software teams building AI agents and applications that answer questions about organizational data. It provides a semantic layer for defining business entities, metrics, relationships, and dimensions, then uses those definitions to translate natural-language questions into executable SQL. Teams can expose Dosi to compatible agents through the Model Context Protocol (MCP), or use its command-line interface and local server in developer workflows. Dosi connects to supported analytical databases and data warehouses, allowing queries to run against configured data sources while keeping business definitions consistent. Its intended uses include governed conversational analytics, agent-powered data exploration, and adding structured business context to AI-driven data applications.Starting Price: $0 -
12
Actian AI Analyst
Actian
Actian AI Analyst is a context-aware conversational analytics platform designed to help organizations get trusted answers from their data using natural language. It enables business users to ask questions directly without writing SQL, transforming traditional dashboards into an interactive, ongoing conversation with data. It operates on a governed semantic layer that models business metrics, relationships, and definitions before analysis begins, ensuring that every query is grounded in how the organization actually works. This semantic layer is automatically generated and maintained by the Steward AI agent, which continuously monitors data definitions and connections, providing reviewable action plans to maintain accuracy over time. AI Analyst preserves conversational context across follow-up questions, allowing deeper exploration while keeping results consistent with defined business logic. -
13
Solid
Solid
Solid is an AI-powered data intelligence platform designed to make enterprise data reliable and ready for use across AI, analytics, and “chat with your data” experiences. It automatically discovers, documents, and builds business-aware semantic models from a company’s existing data, queries, and tools, creating a consistent foundation that AI systems can trust. It analyzes how data is actually used within the organization and generates validated tables, metrics, relationships, and SQL logic aligned with real business definitions. Through products such as Solid Build and Solid Analyze, teams can automate semantic modeling, translate natural-language questions into production-ready SQL, and keep models continuously updated as data changes. It emphasizes transparency and human oversight, allowing data teams to review, edit, and validate AI-generated models rather than relying on opaque automation. -
14
Cube
Cube Dev
Cube is an AI-powered business intelligence and semantic layer platform that helps organizations access, analyze, and govern business data across applications and AI agents. The software connects to data warehouses, databases, and other data sources to create a centralized semantic model containing standardized metrics, dimensions, relationships, and business definitions. Its AI-powered analytics capabilities allow users to ask questions in natural language, generate reports, build dashboards, and explore data without writing complex SQL queries. Cube provides Model Context Protocol (MCP) integrations that enable AI assistants such as ChatGPT, Claude, and Cursor to retrieve governed business information and perform analytical tasks. Its query acceleration engine uses caching and pre-aggregations to improve analytics performance while maintaining consistent data access controls. -
15
Codd AI
Codd AI
Codd AI solves one of the biggest problems in analytics: making data truly business-ready. Instead of teams spending weeks manually mapping schemas, building models, and defining metrics, Codd uses generative AI to automatically create a context-aware semantic layer that aligns technical data with your business language. That means business users can ask questions in plain English and get accurate, governed answers instantly—through BI tools, conversational AI, or any endpoint. With governance and auditability built in, Codd makes analytics faster, clearer, and more trustworthy. Codd AI ingests both technical metadata from your database, as well as business rules and logic to use AI to auto-generate the most comprehensive semantic layer. This semantic layer is embedded in an intelligent query agent to power natural language (NLP) conversational analytics or power traditional BI toolsStarting Price: $25k per year -
16
Ardent
Ardent
Ardent (at tryardent.com) is an AI data engineer platform that builds, maintains, and scales data pipelines with minimal human effort. It lets users issue natural language commands, and the system handles implementation, schema inference, lineage tracking, and error resolution autonomously. Ardent’s ingestors come preconfigured for many common data sources and work “out of the box,” enabling connection to warehouses, orchestration systems, and databases in under 30 minutes. It supports debugging on autopilot by referencing web and documentation knowledge, and is trained on thousands of real engineering tasks to solve complex pipeline issues with zero intervention. It is engineered to handle production contexts, managing numerous tables and pipelines at scale, running parallel jobs, triggering self-healing workflows, monitoring and enforcing data quality, and orchestrating operations through APIs or UI.Starting Price: Free -
17
Verdonz
Verdonz
Verdonz is a business intelligence and AI analytics platform for teams investigating performance and business data. It connects to warehouses, databases, query engines, monitoring systems, and knowledge sources, organizing metrics, entities, relationships, and access rules in a shared semantic model. Users ask natural-language questions, inspect metric definitions and SQL behind answers, and explore dashboards, reports, and alerts based on governed metrics. Configurable AI agents investigate connected data and knowledge on demand, on a schedule, or after alerts; external assistants access approved context through the read-only Model Context Protocol (MCP) server or API. Embedded analytics can expose saved queries in other applications. Verdonz is available as hosted SaaS, in a dedicated instance or customer cloud, and as self-hosted software for organizations that need infrastructure control.Starting Price: $199/user/month -
18
Databricks Genie Code
Databricks
Genie Code is an AI agent built for data teams that analyzes, builds, and maintains complex data workflows inside the Databricks workspace. It autonomously plans and executes multistep tasks while adapting to an organization’s data and governance model, with specialized capabilities across data engineering, data science, machine learning, and business intelligence. Grounded in Unity Catalog metadata, semantics, and governance, it can identify authoritative tables, metrics, and assets, understand dependencies across data and AI systems, and respect existing access controls. For data science, Genie Code can find and clean data, explore datasets, test hypotheses, and generate shareable reports. Machine learning workflows include feature engineering, model training and evaluation, deployment, endpoint configuration, and performance tuning. Data engineers can use natural language to automate ETL workloads, optimize queries, and build Spark Declarative Pipelines. -
19
Ask On Data
Helical Insight
Ask On Data is a chat based AI powered open source Data Engineering/ ETL tool. With agentic capabilities and pioneering next gen data stack, Ask On Data can help in creating data pipelines via a very simple chat interface. It can be used for tasks like Data Migration, Data Loading, Data Transformations, Data Wrangling, Data Cleaning as well as Data Analysis as well with a simple chat interface. This tool can be used by Data Scientists to get clean data. Data Analyst and BI engineers to create calculated tables. Data Engineers can also use this tool to increase their efficiency and achieve much more. -
20
Strategy Mosaic
Strategy Software
Strategy Mosaic is an AI-powered universal semantic data layer and analytics foundation that sits on top of an organization’s existing data systems to unify, govern, and accelerate access to business data for analytics, AI, and reporting without costly restructuring. It creates a single source of truth with consistent business definitions, metrics, and security policies across tools and sources, harmonizing data from hundreds of systems so insights are reliable and comparable everywhere. Built with AI-assisted data modeling (Mosaic Studio), Mosaic automates data preparation, cleansing, enrichment, and modeling, reducing the time and effort needed to build robust data products and semantic models. Its universal connectors let users access governed data via SQL, REST, Python, or through popular BI and productivity tools like Power BI, Tableau, Excel, and Google Sheets, while an in-memory acceleration engine delivers fast query performance across diverse sources. -
21
Microsoft Fabric
Microsoft
Reshape how everyone accesses, manages, and acts on data and insights by connecting every data source and analytics service together—on a single, AI-powered platform. All your data. All your teams. All in one place. Establish an open and lake-centric hub that helps data engineers connect and curate data from different sources—eliminating sprawl and creating custom views for everyone. Accelerate analysis by developing AI models on a single foundation without data movement—reducing the time data scientists need to deliver value. Innovate faster by helping every person in your organization act on insights from within Microsoft 365 apps, such as Microsoft Excel and Microsoft Teams. Responsibly connect people and data using an open and scalable solution that gives data stewards additional control with built-in security, governance, and compliance.Starting Price: $156.334/month/2CU -
22
Colrows
Colrows
Colrows is an autonomous semantic layer engineered to make enterprise AI reliable at production scale. Enterprise AI initiatives stall when models hallucinate and answers lack auditability. Colrows fixes the context, not the model. The platform continuously crawls databases, warehouses, catalogs, and documentation to build a dynamic business graph of entities, metrics, and logic. Sitting between enterprise data and AI surfaces, Colrows compiles natural language into governed, auditable SQL query plans. Every output traces directly to a verified single source of truth. Key capabilities include: AI Data Analyst: Conversational analytics with end-to-end SQL lineage. Semantic API: Standardized semantic infrastructure for internal copilots and agents. Auto-Crawl Engine: Continuous metadata synchronization without manual coding. Colrows delivers the mathematical accuracy and regulatory defensibility that probabilistic RAG cannot match. It is suited for regulated industries.Starting Price: $70/user/month -
23
Prophecy
Prophecy.ai
Prophecy is an AI-powered data preparation and analysis platform that enables business users to transform raw data into actionable insights through natural language prompts. The platform uses specialized AI agents to automatically generate visual, low-code data workflows that users can inspect, refine, validate, and deploy without requiring programming expertise. Prophecy connects directly to cloud data platforms such as Databricks, Snowflake, and BigQuery, allowing organizations to prepare, analyze, and govern data at enterprise scale. The platform combines AI-generated data pipelines with visual workflow interfaces, making complex data transformations easier to understand and manage. Users can automate data preparation, perform advanced analysis, create visualizations, and deploy production-ready workflows while maintaining governance and transparency.Starting Price: $150/user/month -
24
Dremio
Dremio
Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable. -
25
Numbers Station
Numbers Station
Accelerating insights, eliminating barriers for data analysts. Intelligent data stack automation, get insights from your data 10x faster with AI. Pioneered at the Stanford AI lab and now available to your enterprise, intelligence for the modern data stack has arrived. Use natural language to get value from your messy, complex, and siloed data in minutes. Tell your data your desired output, and immediately generate code for execution. Customizable automation of complex data tasks that are specific to your organization and not captured by templated solutions. Empower anyone to securely automate data-intensive workflows on the modern data stack, free data engineers from an endless backlog of requests. Arrive at insights in minutes, not months. Uniquely designed for you, tuned for your organization’s needs. Integrated with upstream and downstream tools, Snowflake, Databricks, Redshift, BigQuery, and more coming, built on dbt. -
26
Beye
Beye
Beye is an AI-native generative business intelligence platform that ingests and auto-cleans raw data from spreadsheets, ERPs, and cloud apps, into unified, AI-optimized dataverses in weeks rather than months. Its generative BI agent auto-builds your first data model and starter dashboards around your specific use case, applying metadata and semantic layers, measure creation, and data preparation without manual effort. Business users, managers, and executives can ask questions in plain English, no SQL or dashboard navigation required, to receive instant, high-fidelity analytics, contextualized insights, and root-cause explanations with traceable queries. It integrates seamlessly with SAP, Snowflake, Salesforce, NetSuite, and over 50 additional sources, supports collaborative channels and custom metrics, and validates answers through AI-driven workflows. -
27
PandaAI
PandaAI
PandaAI is an AI-driven platform that transforms natural language queries into actionable data insights, streamlining the data analysis process. It allows users to connect databases effortlessly, enabling instant report generation through agentic AI and text-to-SQL layers. Users can interact with their data using conversational AI, facilitating intuitive, human-like queries. It also supports team collaboration by allowing users to save responses as data snippets and share them with colleagues. To get started, users can install the pandasai Python library, set up their API key, load their datasets, and push them to the platform for analysis.Starting Price: €20 per month -
28
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 -
29
Genloop
Genloop Labs Inc
Genloop is an intelligence layer between your entire data estate and every human or AI agent that needs to reason about it — connecting live to Snowflake, BigQuery, and lakehouse sources, no ETL, no copies, reasoning across all of them in a single query. Liveboards — free automated reports on live data, no setup Proactive monitoring — agents watch metrics and surface findings before you ask Living Context Graph — captures what data means, how the business investigates, and who's asking, so the same question gets the same verified answer every time Decision Intelligence — tracks actions and outcomes post-answer, feeding back into the graph so future suggestions are grounded in what's actually worked Compounding, not just answering — each layer sharpens the next; Genloop gets more accurate with use instead of resetting every session #1 on Spider 2.0-Snow (96.70%) — the hardest public benchmark for enterprise text-to-SQL reasoningStarting Price: $20/month -
30
Basedash
Basedash
Basedash is an AI-native business intelligence platform that enables teams to build dashboards, charts, reports, and data insights using natural language instead of complex manual processes. The platform connects to data warehouses and hundreds of business applications, allowing users to analyze information from multiple sources in one centralized workspace. AI-powered dashboards, semantic metrics, and automated reporting help organizations generate trusted insights quickly while reducing the need for SQL expertise. Basedash includes a semantic layer that ensures metrics remain consistent across reports, helping teams make decisions using verified business data. Built-in security features such as encryption, role-based access control, SSO, SCIM, and SOC 2 compliance help organizations protect sensitive information. By combining AI, analytics, automation, and data integration into one platform, Basedash helps businesses turn raw data into actionable intelligence in minutes.Starting Price: $1000/month -
31
Snowflake Cortex AI
Snowflake
Snowflake Cortex AI is a fully managed, serverless platform that enables organizations to analyze unstructured data and build generative AI applications within the Snowflake ecosystem. It offers access to industry-leading large language models (LLMs) such as Meta's Llama 3 and 4, Mistral, and Reka-Core, facilitating tasks like text summarization, sentiment analysis, translation, and question answering. Cortex AI supports Retrieval-Augmented Generation (RAG) and text-to-SQL functionalities, allowing users to query structured and unstructured data seamlessly. Key features include Cortex Analyst, which enables business users to interact with data using natural language; Cortex Search, a hybrid vector and keyword search engine for document retrieval; and Cortex Fine-Tuning, which allows customization of LLMs for specific use cases.Starting Price: $2 per month -
32
GoodData.AI
GoodData.AI
GoodData.AI is an AI-ready analytics platform that helps organizations turn data into actionable insights through business intelligence, embedded analytics, and governed semantic modeling. It enables businesses to build dashboards, AI-powered applications, and intelligent workflows using a composable architecture designed for enterprise environments. The platform provides a centralized semantic layer that ensures consistent business logic across reports, analytics, AI agents, and embedded experiences. GoodData supports cloud and on-premises deployments while integrating with modern data ecosystems and enterprise applications. It also includes AI capabilities for conversational analytics, automation, decision support, and custom agent development. With enterprise-grade security, compliance certifications, and extensive developer tools, GoodData is designed to help organizations modernize their analytics infrastructure for the AI era. -
33
Xtract Data Automation Suite (XDAS)
Xtract.io
Xtract Data Automation Suite (XDAS) is a comprehensive platform designed to streamline process automation for data-intensive workflows. It offers a vast library of over 300 pre-built micro solutions and AI agents, enabling businesses to design and orchestrate AI-driven workflows with no code environment, thereby enhancing operational efficiency and accelerating digital transformation. Key components of XDAS include Bot Studio, which allows users to create custom bots and scripts; Scrape Studio, for effortless web data extraction; GenAI Studio, for developing AI agents that process unstructured data; HITL Studio, which integrates human oversight into data workflows; and XRAG Studio, for building advanced AI systems using retrieval-augmented generation techniques. By leveraging these tools, XDAS helps businesses ensure compliance, reduce time to market, enhance data accuracy, and forecast market trends across various industries. -
34
Zinzu
Zinzu
Zinzu is a cloud-based, no-code data analytics platform designed to help organizations uncover hidden patterns in sequential data through a user-friendly drag-and-drop interface. By treating each data record as an event in a timeline, Zinzu enables businesses to analyze complex sequences without the need for complex queries. The platform integrates seamlessly with major cloud providers, allowing users to connect directly to their existing data sources without the need for data migration. Zinzu's AI-powered query engine supports natural language processing, enabling users to express data queries in everyday language. It operates on a pay-as-you-go model, ensuring flexibility and cost-efficiency. Zinzu is particularly beneficial for applications such as tracking campaign performance, monitoring customer journeys, detecting fraud, and optimizing supply chains. -
35
Databao
JetBrains
Databao is an AI-powered agentic analytics platform designed to help organizations connect databases, BI tools, documents, and spreadsheets into a governed semantic layer that enables reliable natural language querying and analytics. The platform allows technical and business users to ask questions in plain language and receive accurate, reproducible answers without relying on manual dashboard creation, SQL writing, or ad-hoc analytics requests. Databao includes open-source tools such as Context Engine, Data Agent, and an Analytics CLI that work together to generate semantic context from enterprise data sources, automate SQL generation, query multiple datasets, clean and visualize data, and orchestrate conversational analytics workflows. The platform supports local deployment within an organization’s environment and integrates with large language models to reduce SQL hallucinations, improve query accuracy, and streamline data workflows.Starting Price: Free -
36
Querona
YouNeedIT
We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems. If you have ever experienced a lack of data you needed, time to consuming report generation or long queue to your BI expert, consider Querona. Querona uses a built-in Big Data engine to handle growing data volumes. Repeatable queries can be cached or calculated in advance. Optimization needs less effort as Querona automatically suggests query improvements. Querona empowers business analysts and data scientists by putting self-service in their hands. They can easily discover and prototype data models, add new data sources, experiment with query optimization and dig in raw data. Less IT is needed. Now users can get live data no matter where it is stored. If databases are too busy to be queried live, Querona will cache the data. -
37
Lumi AI
Lumi AI
Lumi AI is an enterprise analytics platform that enables users to explore data and extract custom insights through natural language queries, eliminating the need for SQL or Python expertise. It offers self-service analytics, conversational analytics, customizable visualizations, knowledge management, seamless integrations, and robust security features. Lumi AI supports diverse teams, including data analysis, supply chain management, procurement, sales, merchandising, and financial planning, by providing actionable insights tailored to unique business terms and metrics. Its agentic workflows address simple to complex queries, uncover root causes, and facilitate complex analyses, all while interpreting business-specific language. Lumi AI integrates effortlessly with various data sources, ensuring enterprise-grade security by processing data within the client's network and offering advanced user permissions and query controls. -
38
Iterative
Iterative
AI teams face challenges that require new technologies. We build these technologies. Existing data warehouses and data lakes do not fit unstructured datasets like text, images, and videos. AI hand in hand with software development. Built with data scientists, ML engineers, and data engineers in mind. Don’t reinvent the wheel! Fast and cost‑efficient path to production. Your data is always stored by you. Your models are trained on your machines. Existing data warehouses and data lakes do not fit unstructured datasets like text, images, and videos. AI teams face challenges that require new technologies. We build these technologies. Studio is an extension of GitHub, GitLab or BitBucket. Sign up for the online SaaS version or contact us to get on-premise installation -
39
Apache Ossie
Apache Software Foundation
Apache Ossie is an open specification and converter toolkit for exchanging semantic metadata across analytics, business intelligence, and AI systems. Its YAML-based format describes semantic models, datasets, fields, metrics, dimensions, relationships, and SQL expressions in a portable structure. Data and analytics engineers can use compatible implementations to author, translate, and reuse these definitions across connected platforms, supporting consistent business context for reporting and AI-assisted analysis. The project is an open-source community effort under the Apache License 2.0, with available conversions depending on each platform’s implementation. -
40
Presto
Presto Foundation
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. For data engineers who struggle with managing multiple query languages and interfaces to siloed databases and storage, Presto is the fast and reliable engine that provides one simple ANSI SQL interface for all your data analytics and your open lakehouse. Different engines for different workloads means you will have to re-platform down the road. With Presto, you get 1 familar ANSI SQL language and 1 engine for your data analytics so you don't need to graduate to another lakehouse engine. Presto can be used for interactive and batch workloads, small and large amounts of data, and scales from a few to thousands of users. Presto gives you one simple ANSI SQL interface for all of your data in various siloed data systems, helping you join your data ecosystem together. -
41
AtScale
AtScale
AtScale helps accelerate and simplify business intelligence resulting in faster time-to-insight, better business decisions, and more ROI on your Cloud analytics investment. Eliminate repetitive data engineering tasks like curating, maintaining and delivering data for analysis. Define business definitions in one location to ensure consistent KPI reporting across BI tools. Accelerate time to insight from data while efficiently managing cloud compute costs. Leverage existing data security policies for data analytics no matter where data resides. AtScale’s Insights workbooks and models let you perform Cloud OLAP multidimensional analysis on data sets from multiple providers – with no data prep or data engineering required. We provide built-in easy to use dimensions and measures to help you quickly derive insights that you can use for business decisions. -
42
Bruin
Bruin Data
Bruin is a data platform for data and analytics engineering teams that combines data ingestion, transformation, orchestration and analytics workflows. Teams define pipelines as code in a Git repository using SQL, Python or R, with dependencies, materializations and data-quality checks managed alongside assets. Built-in connectors move data from databases, warehouses, SaaS tools, files and APIs into supported destinations; transformations run in the connected warehouse. Bruin Cloud adds managed scheduling, run monitoring, lineage, a data catalog, access controls and usage tracking, while the open-source CLI can run locally, in CI, in a team's cloud environment or on-premises. An AI data analyst answers questions from governed warehouse data in chat or the browser and can show the SQL behind its answers. Teams can also create dashboards, data apps and scheduled agents from shared data.Starting Price: $0.01/credit -
43
Brewit
Brewit
Make data-driven decisions 10x faster with self-service analytics. Integrate with your databases and data warehouses all-in-one place (Postgres, MySQL, Snowflake, BigQuery, and more). Brewit can write SQL queries and create recommended charts based on your data questions. It also helps you drill down on the analysis. Chat with your database, visualize insights, & perform analysis. Ensure answer accuracy and consistency with a built-in data catalog. An automated semantic layer that ensures Brewit answers with correct business logic. Easily manage your data catalog & data dictionary. Building a beautiful report is as easy as writing a doc. Data without a story is useless. Our Notion-style notebook editor allows you to create reports & dashboards easily, turning raw data into actionable insights. All organized data products are usable by anyone who has a data question, regardless of their technical skills. -
44
ClarityQ
ClarityQ Inc
ClarityQ is an AI data analytics platform for data, product, and business teams. It connects to warehouses such as Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, Athena, and Azure Synapse, where users ask questions in natural language and receive analysis, visualizations, insights, and action plans without remodeling data. Its automatically maintained Context Layer organizes business logic, metric definitions, and table relationships, with changes tracked for review. Answers can show reasoning, generated SQL, and data sources; validation checks results, and follow-up questions clarify ambiguity. Teams create dashboards from prompts, schedule reports to Slack or email, and share results with role-aware access controls. The platform is read-only by default and offers an open API, SOC 2 Type II and GDPR compliance, Private Link, and single-tenant options. Use cases include product, growth, and business analysis for gaming, SaaS, e-commerce, and consumer app companies.Starting Price: $499/month -
45
Snowflake CoCo
Snowflake
Snowflake CoCo is a data-native AI coding agent that turns complex data engineering, analytics, machine learning, and AI workflows into simple conversations. It understands enterprise context, including catalog, lineage, RBAC policies, compute, and pipeline dependencies, helping generated code reference real objects with the correct permissions. Teams can use CoCo to identify data, build pipelines across dbt, Apache Airflow, Postgres, Spark, and AWS Glue, generate executable ML pipelines for Snowflake Notebooks, and create apps and AI agents grounded in enterprise data. Its agent harness includes Snowflake-specialized tools such as semantic catalog search, data diffing, and sandboxed runtimes rather than relying on generic code wrappers. For complex, multi-step tasks, orchestration can coordinate sub-agents and route between models automatically. CoCo is available as a desktop development environment with access to local files, terminals, and Snowflake.Starting Price: $2 per credit -
46
Trace
Trace
Trace is an automated KPI analysis platform that helps teams see exactly why business metrics move without chasing dashboards or waiting days for answers. It uses metric trees to connect KPIs with their underlying drivers in a shared, computable model of performance, making analysis repeatable, explainable, and suitable for reliable AI-powered insights. Trace decomposes performance, attributes changes, ranks the most important drivers, compares results with plan, detects anomalies, and scans segments so teams can move from a question to a clear explanation in minutes. Unlike dashboards that only show what happened or AI copilots that still depend on users to direct the investigation, Trace encodes analytical skills that allow its AI agent to perform the analyst workflow autonomously. Teams can begin with one or two critical KPIs, use editable templates, and connect the platform to their warehouse without migrating or restructuring data. -
47
SplineCloud
SplineCloud
SplineCloud is an open knowledge management platform designed to facilitate the discovery, formalization, and exchange of structured and reusable knowledge in science and engineering. It enables users to organize data into structured repositories, making it findable and accessible. The platform offers tools such as an online plot digitizer for extracting data from graphs and an interactive curve fitting tool that allows users to define functional relationships in datasets using smooth spline functions. Users can also reuse datasets and relations in their models and calculations by accessing them directly through the SplineCloud API or by utilizing open source client libraries for Python and MATLAB. The platform supports the development of reusable engineering and analytical applications, aiming to reduce redundancy in design processes, preserve expert knowledge, and facilitate better decision-making. -
48
Archon Data Store
Platform 3 Solutions
Archon Data Store is a next-generation enterprise data archiving platform designed to help organizations manage rapid data growth, reduce legacy application costs, and meet global compliance standards. Built on a modern Lakehouse architecture, Archon Data Store unifies data lakes and data warehouses to deliver secure, scalable, and analytics-ready archival storage. The platform supports on-premise, cloud, and hybrid deployments with AES-256 encryption, audit trails, metadata governance, and role-based access control. Archon Data Store offers intelligent storage tiering, high-performance querying, and seamless integration with BI tools. It enables efficient application decommissioning, cloud migration, and digital modernization while transforming archived data into a strategic asset. With Archon Data Store, organizations can ensure long-term compliance, optimize storage costs, and unlock AI-driven insights from historical data. -
49
GetDot.ai
Snowboard Software GmbH
Dot (getdot.ai) is an AI data analyst. People ask in plain English in Slack, Microsoft Teams, the web app, or from AI agents through its MCP server and CLI. Dot finds the right tables, writes and runs SQL on the company's own warehouse, and answers with charts, data and the SQL it ran. Data teams train it with notes, dbt and semantic-layer context and evaluations, and a Context Agent keeps that knowledge current. It also builds data apps and scheduled reports. SOC 2 Type II and GDPR compliant.Starting Price: Free -
50
Compass
Dagster Labs
Compass is an AI-powered, Slack-native data assistant that turns plain English questions into instant answers, summaries, charts, and insights powered by your actual warehouse data, so teams can make data-driven decisions without waiting on BI backlogs or building dashboards first. It connects directly to major data warehouses (Snowflake, BigQuery, Redshift, Postgres, AWS Athena, Databricks, and more), learns your schema and context, and generates governed, SQL-backed responses and visualizations in the tools your team already uses, all while keeping your data where it lives and under your control. Compass builds organizational context over time so answers become more accurate and relevant, supports collaboration through Slack threads, can schedule recurring analysis, and provides a shared repository of definitions and insights that help reduce analytical silos and reliance on specialized SQL users.Starting Price: $49 per month
