Best Dbms 2025

Based on monthly keyword-search data

Featured Dbms 2025
Rank Product Monthly VolumeVol 3-Month GrowthGrowth
1 Duckdb DuckDB accelerates in-process analytics with columnar SQL dbms for fast joins and ETL 6.3M +14%
  DuckDB accelerates in-process analytics with columnar SQL dbms for fast joins and ETL
2 Supabase Supabase offers managed Postgres; optimize queries, scale, and secure data easily 117.3K +20%
  Supabase offers managed Postgres; optimize queries, scale, and secure data easily
3 Airtable Airtable offers a flexible cloud DBMS to model, query, and share data with ease. 168.3K +6%
  Airtable offers a flexible cloud DBMS to model, query, and share data with ease.
4 Pinecone Pinecone scales a managed vector DB to index embeddings and optimize semantic search 62.7K +11%
  Pinecone scales a managed vector DB to index embeddings and optimize semantic search
5 Firebase Firebase scales NoSQL storage with Firestore and Realtime Database for agile apps 90.5K -1%
  Firebase scales NoSQL storage with Firestore and Realtime Database for agile apps
Top 5 Dbms by Monthly Volume
Rank Product Monthly VolumeVol 3-Month GrowthGrowth
1 Duckdb DuckDB accelerates in-process analytics with columnar SQL dbms for fast joins and ETL 6.3M +14%
  DuckDB accelerates in-process analytics with columnar SQL dbms for fast joins and ETL
2 Airtable Airtable offers a flexible cloud DBMS to model, query, and share data with ease. 168.3K +6%
  Airtable offers a flexible cloud DBMS to model, query, and share data with ease.
3 Supabase Supabase offers managed Postgres; optimize queries, scale, and secure data easily 117.3K +20%
  Supabase offers managed Postgres; optimize queries, scale, and secure data easily
4 Firebase Firebase scales NoSQL storage with Firestore and Realtime Database for agile apps 90.5K -1%
  Firebase scales NoSQL storage with Firestore and Realtime Database for agile apps
5 Pinecone Pinecone scales a managed vector DB to index embeddings and optimize semantic search 62.7K +11%
  Pinecone scales a managed vector DB to index embeddings and optimize semantic search
Top 5 Dbms by 3‑Month Growth
Rank Product Monthly VolumeVol 3-Month GrowthGrowth
1 Kinetica Kinetica offers a GPU-accelerated DBMS to analyze streaming, geospatial data at real-time scale. 6.3K +48%
  Kinetica offers a GPU-accelerated DBMS to analyze streaming, geospatial data at real-time scale.
2 Qdrant Qdrant powers a high-performance vector DB to scale semantic search and RAG systems 8.7K +23%
  Qdrant powers a high-performance vector DB to scale semantic search and RAG systems
3 Supabase Supabase offers managed Postgres; optimize queries, scale, and secure data easily 117.3K +20%
  Supabase offers managed Postgres; optimize queries, scale, and secure data easily
4 Planetscale PlanetScale delivers serverless MySQL; automate scaling, branching, and high-availability. 8.5K +16%
  PlanetScale delivers serverless MySQL; automate scaling, branching, and high-availability.
5 Duckdb DuckDB accelerates in-process analytics with columnar SQL dbms for fast joins and ETL 6.3M +14%
  DuckDB accelerates in-process analytics with columnar SQL dbms for fast joins and ETL

Methodology

  • Analysis periods: Monthly to 3‑month timelines for trend tracking
  • Ranking factors: Search volume, growth rate, keyword relevance
  • Validation process: Cross‑checking metrics across multiple sources
  • Quality assurance: Multi‑source verification for accuracy
  • Update frequency: Daily refresh at 00:00 UTC

Sources

  • Google Analytics: Primary keyword data collection
  • Google Trends: Search volume and trend analysis
  • Google Keyword Planner: Search metrics validation
  • Third‑party analytics: Additional verification platforms

Frequently Asked Questions

Will AI take my job?

AI is likely to replace jobs that do not require human elements such as empathy or creativity (such as a therapist or an artist). However, commercial AI adoption and job displacement will not happen as fast as many believe. Most people won't notice a change for at least 2-3 years, with a major economic shift happing over the next decade. This means you have time to adapt, ideally learning to use AI to your advantage in order to remain productive.

How does AI actually work?

Most models learn patterns from data rather than "understanding" like humans. For example, AI has learned that when it sees: "Think outside the..." it will have learned to predict the next word to be "box". As technology advances, and more data centers are built, AI will continuously improve on its pattern recognition skills.

Can I trust AI answers? What about bias and hallucinations?

You can trust AI answers like you trust a human's answers — with the understanding that even humans with the best intentions can be wrong sometimes. However, as AI technology advances, these mistakes will become less frequent, eventually to the point of near perfection.

Is my data safe when I use AI tools?

Your data is stored on the server of whichever company's product you are using, unless you are running an open-source AI model on your personal computer. "Safe" can be an objective term, depending how much you trust that company to protect your data.

Is AI sentient or close to AGI?

Not yet, but most experts agree that AGI is only a matter of time. Some believe AGI, a term used to mark the moment in which artificial intelligence surpasses human intelligence, will be achieved in as few as 2-3 years, while other say 5-10 years.

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