Elastic vs Neo4j
Who this is for
If you're weighing Elastic against Neo4j in Databases, this page is for you. It puts the facts from both Techarda profiles side by side, with each company's recent stories and any community threads that name them both. It doesn't pick a winner: the questions further down come from our evaluation guide, so you can put the same ones to both.
Stories and counts cover the last 90 days, counted on 23 Oct 2026. Profiles last updated 27 Sept 2026. Want a different line-up? The interactive compare tool takes up to four companies.
The facts side by side
From each company's Techarda profile. Categories they share are marked, with each company's position in the category's leader list.
| Elastic | Neo4j | |
|---|---|---|
| Founded | 2012 | 2007 |
| Headquarters | San Francisco, California, USA | San Mateo, California, USA |
| Categories |
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| What they do | Elastic is the company behind Elasticsearch, Kibana, Logstash and Beats, collectively known as the Elastic Stack. Founded in 2012 by Shay Banon and others, it is incorporated in the Netherlands and operates as a distributed company with a US headquarters in San Francisco. It offers search, observability and security… | Neo4j is a graph database and analytics company whose flagship Neo4j graph database stores and queries connected data using the Cypher query language. Its offerings include AuraDB, a fully managed cloud service, Graph Data Science for graph algorithms and machine learning, and tooling for GraphRAG and knowledge… |
| Official site | elastic.co | neo4j.com |
| Stories, last 90 days | 33 | 31 |
Recent stories from each
What each company has published in the last 90 days, newest first. Each story links to the original source.
How to choose between them
We don't score or rank these two. The questions below come from our Databases evaluation guide, and they work best when you put each one to both companies and compare the answers side by side.
Fit with your data model and access patterns
Many database problems trace back to a model that does not match how the application reads and writes. Fit matters more than feature lists.
Ask both: Here are our main queries and write patterns: which would be fast on your database, which would be slow, and what would you change in our design?
Behaviour under failure
Every database looks reliable when nothing is wrong. What matters is what happens to in-flight transactions when a node, zone or region fails.
Ask both: What consistency do we get during a node or region failure, how long does failover take in practice, and can we cause that failure ourselves during the trial?
Licence and project governance
A licence change can affect what you may run, who may offer it as a service and what support will cost.
Ask both: Which licence covers the version we would run, who controls the project, and what commitments do you make about future licence terms?
Operating cost at your scale
Storage, I/O, replicas, backups and cross-region traffic often cost more than the compute line on the quote.
Ask both: What would our workload cost each month including replicas, backups, I/O and data transfer, and how does that change if our data doubles?
Migration and compatibility
Moving data is the easy part. Rewriting queries, stored procedures and application code is where the time goes.
Ask both: Which of our queries, procedures and drivers work unchanged, what migration tooling do you provide, and how would we run both systems in parallel?
Backup and point-in-time recovery
Recovery is the feature tested least and needed at the worst moment. Restoring a large database can take far longer than people expect.
Ask both: How long does a full restore of a database our size take, can we restore to a point in time in another region, and can we test it during the trial?
Security and access
Databases hold the data attackers want. Encryption, auditing and identity integration need to work without custom scripts.
Ask both: How do you integrate with our identity provider, who holds the encryption keys, and what does the audit log capture and keep?
Data portability and exit
Proprietary query languages and features make leaving expensive. You should know the cost of exit before you sign.
Ask both: How do we export all of our data and schema in a standard format, how long would that take at our size, and what would it cost?
The guide also lists red flags to watch for in any Databases vendor, and how to build a shortlist.
Keep going
Each profile has the full detail, and the alternatives pages show who else sits in the same categories.
How this page is put together
Every fact comes from the two Techarda profiles, which our editors check against each company's own site and public records. Rows are left out when neither profile has the detail. Stories are the ones each company published in the last 90 days; review counts include published, moderated reviews only.
Something wrong or out of date? Email engage@techarda.com. Used one of them in production? A short review of Elastic or Neo4j helps the next team decide.