Vecstore vs Elasticsearch

One is a search API. The other is a search project.

Elasticsearch can do almost anything, if someone on your team runs it. Vecstore works out of the box.

100 free credits on sign up. No card required.

What you skip

5 things you don't have to run with Vecstore

1/ The embedding step

Elasticsearch can store vectors, but you still make them yourself. Vecstore takes plain text and handles the rest.

Elasticsearch

// 1. Generate embedding
const embedding = await openai.embeddings
  .create({
    model: 'text-embedding-3-small',
    input: query
  });

// 2. Build hybrid query
const results = await client.search({
  index: 'products',
  knn: {
    field: 'embedding',
    query_vector: embedding.data[0].embedding,
    k: 10
  },
  query: { match: { title: query } }
});

Vecstore

const results = await fetch(
  `https://api.vecstore.app/databases/${dbId}/search`,
  {
    method: 'POST',
    headers: {
      'X-API-Key': apiKey,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({ query })
  }
);

2/ A cluster

No nodes, shards, replicas or heap sizes. Nobody on your team becomes "the Elasticsearch person".

nodesshardsreplicasJVM heap

3/ Relevance tuning

No boosts, analyzers or scoring scripts to tweak until results feel right.

BM25 boostsanalyzersfunction scores

4/ A separate image search

Reverse image, text to image, face and OCR search come with the same API.

Image search → OCR search →

5/ Language analyzers

100+ languages in one index. No analyzer or index per language.

English한국어Deutsch日本語

Side by side

Compare Vecstore vs Elasticsearch

Feature	Vecstore	Elasticsearch
What it is	Search API	Search engine you run
Search type	Semantic + hybrid	Keyword + kNN
Embeddings	Built in	Bring your own
Image search
Languages	100+ in one index	Analyzer per language
NSFW detection
Cluster to manage
Relevance tuning	Automatic	Manual
Log analytics
Complex aggregations
Starting price	$11/mo	Self-hosted or Elastic Cloud

Being honest

Elasticsearch is powerful infrastructure. Vecstore is a finished search product.

Pick Elasticsearch for

✓ Logs and observability
✓ Faceted search with nested aggregations
✓ Full control over analyzers and scoring
✓ A team that already runs it well

Pick Vecstore for

✓ Search that understands meaning
✓ Image search of any kind
✓ No one on call for a cluster
✓ Shipping this week

Common questions

Can Elasticsearch do semantic search?

It supports kNN vector search, but you still create the embeddings, set up vector fields and run that pipeline yourself. Vecstore does that part for you.

What about Elastic Cloud?

It takes away the hosting, not the setup. You still configure mappings, analyzers, relevance and embeddings.

Can Vecstore replace Elasticsearch for logs?

No. Vecstore is for product search, content search and image search. For logs, the ELK stack is the right tool.

What about filters?

Vecstore combines semantic and keyword search in one call, which covers basic filtering. For deep faceted navigation, Elasticsearch gives you more control.

Is it fast at scale?

Searching 10 million records takes 3-4ms. Turning the query into a vector adds about 20ms.

Stop running search infrastructure. Start searching.

85M+ searches powered by Vecstore this year

Start for Free

100 Free credits. No credit card required.