Category 15 software profiles
Data & AI Platforms
Cloud data warehouses, lakehouses, analytics engines and enterprise AI platforms.
Data and AI platforms help organizations turn large, messy collections of information into analysis, predictions and automated decisions. The category includes cloud data warehouses, lakehouse platforms, distributed processing engines, machine learning tooling and ontology-driven analytics software used by governments and large enterprises.
Since the arrival of generative AI, these platforms have become the foundation for building AI applications on private company data, so vendors now compete on governance, security and how easily models can be connected to trusted data. Open-source projects such as Apache Spark and MLflow sit alongside commercial platforms that package them as managed services.
Data & AI Platforms: software on SoftwareLore
- Apache SparkOpen-source engine for large-scale data processing and analytics Databricks 2010 Free and open source
- Databricks Data Intelligence PlatformLakehouse platform for data engineering, analytics, AI and agents Databricks 2014 Usage-based
- MLflowOpen-source platform for tracking, evaluating and deploying ML and AI Databricks 2018 Free and open source
- Palantir AIPPalantir’s platform for putting LLMs and AI agents to work on operations Palantir 2023 Enterprise licensing
- Palantir FoundryOntology-based data operations platform for enterprises and governments Palantir 2016 Enterprise licensing
- Palantir GothamSoftware for defense and intelligence analysis, planning and targeting Palantir 2008 Enterprise licensing
- Snowflake AI Data CloudCloud data platform for analytics, data sharing, apps and AI agents Snowflake 2015 Usage-based
- GitLab DuoGitLab’s AI assistants and agents for the software development lifecycle GitLab 2023 Usage-based
- MongoDB AtlasFully managed MongoDB database service on AWS, Google Cloud and Azure MongoDB 2016 Usage-based
- Oracle Cloud InfrastructureOracle’s public cloud for computing, databases and large AI clusters Oracle 2016 Usage-based
- Oracle DatabaseMulti-model relational database for enterprise transactions and analytics Oracle 1979 Enterprise licensing
- PyCharmJetBrains’ Python IDE for web development, data science and AI JetBrains 2010 Freemium
- SAP HANAIn-memory, column-based database behind SAP’s business applications SAP 2010 Enterprise licensing
- ServiceNow AI PlatformServiceNow’s cloud platform for workflows, low-code apps and AI agents ServiceNow 2006 Subscription
- StreamlitOpen-source Python framework for building interactive data apps Snowflake 2019 Free and open source
Who makes Data & AI Platforms?
What to look for
Questions worth answering before choosing a tool in this category.
- 01
Warehouse, lakehouse or both
Data warehouses excel at structured SQL analytics, while lakehouses also handle raw files, streaming and machine learning on open formats. Many platforms now support both patterns.
- 02
Governance
Fine-grained access control, lineage tracking and auditing are essential when sensitive data feeds dashboards, reports and AI applications.
- 03
Cost model
Most cloud data platforms separate storage from compute and bill for usage. Monitor query and cluster costs closely, because they grow quickly with adoption.
- 04
AI readiness
Evaluate how easily models, vector search and AI agents can be built on governed company data without copying that data into separate systems.
Data & AI Platforms: frequently asked questions
What is the difference between a data warehouse and a data lakehouse?
A data warehouse stores structured, cleaned data optimized for SQL analytics and reporting. A data lakehouse combines the low-cost, flexible storage of a data lake, which holds raw files in open formats, with warehouse-style management and performance, so the same data can serve analytics and machine learning.
What is Apache Spark used for?
Apache Spark is an open-source engine for processing large datasets in parallel across clusters of computers. It is used for data engineering, SQL analytics, streaming and machine learning, and it underpins commercial platforms such as Databricks.
What is an ontology in a data platform?
In platforms such as Palantir Foundry, an ontology maps raw data to real-world objects, like customers, aircraft or shipments, along with their properties, relationships and the actions people can take on them. It lets analysts and applications work with business concepts instead of database tables.
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