ElasticsearchThe search database for AI
vs
PostgreSQLThe world's most advanced open source database
Comparison · Vector Databases · weekly run Nov 2
Elasticsearch vs PostgreSQL
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
PostgreSQL is the stronger AI pick in Vector Databases: it has a visibility score of 49 versus 14.3 for Elasticsearch, and ranks ahead in 73% of the answers that name both.
Choose Elasticsearch if…
- You need SOC 2 Type II or ISO/IEC 27001 or ISO/IEC 27017 or ISO/IEC 27018 or ISO/IEC 27701 or FedRAMP Moderate or FedRAMP High or PCI DSS or HIPAA or CSA STAR coverage
- You prefer a larger, established vendor (1,001–5,000 employees)
- Strongest general enterprise choice for vector search alongside full-text search, logs, and analytics
- Widely deployed, often cited as the most widely deployed vector-capable search engine
Choose PostgreSQL if…
- You want the brand AI engines rank higher (49 vs 14.3)
- AI answers describe it more positively (35% vs 30% positive)
- Free open-source software
- Adds vector search to an existing PostgreSQL database without a new database
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Elasticsearch | PostgreSQL |
|---|---|---|
| Visibility score | 14.3% | 49% |
| Change vs last week | New | New |
| Rank in Vector Databases | #7 | #3 |
| Share of voice | 5.1% | 12.6% |
| Mentions this run | 24 | 59 |
| Positive in AI answers | 30% | 35% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Elasticsearch 0pp · PostgreSQL 0pp over 0 weekly runs.
Engine by engine
PostgreSQL leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
ElasticsearchPostgreSQL
Head to head in AI answers
26 engine answers name both brands
7Elasticsearch ranked higher
19PostgreSQL ranked higher
| Prompt | Engine | Elasticsearch | PostgreSQL |
|---|---|---|---|
| What is a vector database and when does a company need one? | ChatGPT | #6 | #2 |
| What is a vector database and when does a company need one? | AI Mode | #1 | #2 |
| How do I choose a vector database for a mid-market team? | ChatGPT | #7 | #1 |
| How do companies store and search embeddings without a dedicated tool? | ChatGPT | #3 | #1 |
| How do companies store and search embeddings without a dedicated tool? | AI Mode | #4 | #3 |
| How do companies store and search embeddings without a dedicated tool? | Perplexity | #2 | #1 |
| What should a vector database integrate with? | ChatGPT | #3 | #1 |
| What are the best Vector Databases tools in 2026? | ChatGPT | #8 | #5 |
| What are the best Vector Databases tools in 2026? | AI Mode | #7 | #6 |
| What are the best Vector Databases tools in 2026? | Perplexity | #7 | #3 |
| Top vector database options for B2B SaaS companies | Perplexity | #6 | #3 |
| Best vector database for enterprise | Perplexity | #1 | #4 |
Features, pricing & fit
| Dimension | Elasticsearch | PostgreSQL |
|---|---|---|
| Deployment | Elastic Cloud Serverless, Elastic Cloud Hosted, or self-managed on premises, in private, hybrid or air-gapped environments. | — |
| Compliance | SOC 2 Type II, ISO/IEC 27001, ISO/IEC 27017, ISO/IEC 27018, ISO/IEC 27701, FedRAMP Moderate, FedRAMP High, PCI DSS, HIPAA, CSA STAR | — |
| Support | Four support tiers depending on Elastic Cloud subscription tier, 99.95% monthly uptime SLA for Platinum and Enterprise tiers | Community mailing lists, Community events and local user groups |
| Founded | 2012 | — |
| Headquarters | San Francisco, California | United States |
| Employees | 1,001–5,000 | 51–200 |
| Funding | IPO (NYSE) | — |
| Best for | Teams building AI search, RAG and vector applications, and organizations that want search, observability and security on one data platform. | — |
Pros and cons
Themes from the AI answers that mention each brand
Elasticsearch
- Strongest general enterprise choice for vector search alongside full-text search, logs, and analytics
- Widely deployed, often cited as the most widely deployed vector-capable search engine
- Hybrid keyword-plus-semantic search via dense vectors and inverted indexes
- Suited to consolidated stacks and broader search, logging, analytics, or observability platforms
- Existing infrastructure can be leveraged
- Smaller community and ecosystem than PostgreSQL, MySQL, MongoDB
PostgreSQL
- Free open-source software
- Adds vector search to an existing PostgreSQL database without a new database
- Wide compatibility with drivers, BI tools, and language ecosystems
- Broad deployment and transparent self-hosted pricing
- Hosting, backups, and maintenance must be paid for when self-hosted
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Elasticsearch vs PostgreSQL”, https://slateindex.ai/compare/elasticsearch-vs-postgresql, data of Nov 2, 2026. Licence: CC BY 4.0.