Software · head to head
Elasticsearch vs QuestDB

Elasticsearch
Software
The heart of the Elastic Stack for search and analytics
- From
- Free
- Rated
- -

QuestDB
Software
Fast open source time-series database for high throughput ingestion
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Elasticsearch eventual consistency model with 1-second default refresh interval, not suitable for real-time transactional requirements; QuestDB open-source edition lacks high-availability, distributed architecture, and enterprise security features
- They diverge on capability: Elasticsearch covers Full-text Search, QuestDB covers High Throughput Ingestion.
Where they differ
Only the attributes on which Elasticsearch and QuestDB actually diverge.
| Attribute | Elasticsearch | QuestDB |
|---|---|---|
| Pricing model | Unknown | open-source |
| Platforms | Linux, Windows, macOS, Docker, Kubernetes | Docker, Kubernetes, Cloud (AWS, Azure, GCP) |
| Founded | 2010 | 2014 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Elasticsearch
- Full-text Search
- Real-time Analytics
- Distributed Architecture
- RESTful API
- Schema-free JSON
- Aggregations
- Machine Learning
- Kibana
Only in QuestDB
- High Throughput Ingestion
- SQL Support
- Time-series Optimization
- SIMD Vectorization
- Column-oriented Storage
- Built-in Web Console
- InfluxDB Line Protocol
- PostgreSQL
Both cover
- Linux support
- Windows support
- Mac support
- Docker support
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Elasticsearch
- Real-time applicationsnot QuestDB
- Content managementnot QuestDB
- User profilesnot QuestDB
- Mobile backendsnot QuestDB
- Cachingnot QuestDB
QuestDB
- Time-series analytics ingesting up to 20M rows/second from IoT sensors or financial data feedsnot Elasticsearch
- Real-time dashboarding with 32ms time-to-first-row latency for minute-level analyticsnot Elasticsearch
- Applications requiring multi-tier storage (hot ingest, real-time SQL, cold Parquet archive)not Elasticsearch
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Elasticsearch
- Eventual consistency model with 1-second default refresh interval, not suitable for real-time transactional requirements
- No support for ACID transactions or rollbacks; updates delete and re-insert documents
- JVM-dependent architecture requires careful memory management and monitoring to prevent garbage collection issues at scale
QuestDB
- Open-source edition lacks high-availability, distributed architecture, and enterprise security features
- Enterprise edition pricing not published; requires contacting sales for custom quote
- Ingestion limit of 20M rows/sec platform-dependent; may not scale to extreme throughput requirements
Pricing, plan by plan
Elasticsearch
Free- Self-ManagedFree
- Open source
- Self-hosted
- Elasticsearch Cloud$16.4/month
- Managed service
- 14-day free trial
QuestDB
FreeNo published plan breakdown. See the QuestDB review.
Which should you pick?
Choose Elasticsearch if
- You need full-text search.
- You want to start without paying.
- You work on Linux, Windows, macOS, Docker, Kubernetes.
- You also want real-time analytics.
Choose QuestDB if
- You need high throughput ingestion.
- You want to start without paying.
- You work on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
- You also want sql support.
Questions people ask
- Is Elasticsearch or QuestDB better?
- Neither clearly leads. Elasticsearch starts at Free and QuestDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Elasticsearch or QuestDB?
- Elasticsearch starts at Free and QuestDB at Free.
- Does Elasticsearch or QuestDB run on more platforms?
- Elasticsearch runs on Linux, Windows, macOS, Docker, Kubernetes. QuestDB runs on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
- Can I use Elasticsearch for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Elasticsearch best used for?
- Elasticsearch is most often used for real-time applications, content management, user profiles, mobile backends. Of those, real-time applications and content management are not what QuestDB is typically brought in for.
- What can Elasticsearch do that QuestDB cannot?
- Elasticsearch covers Full-text Search, Real-time Analytics, Distributed Architecture, RESTful API. QuestDB covers High Throughput Ingestion, SQL Support, Time-series Optimization, SIMD Vectorization. Both handle Linux support, Windows support, Mac support, Docker support.
Answered from the vendors’ own pages
Elasticsearch: Is Elasticsearch free?
Yes, Elasticsearch can be deployed as free and open-source software for self-managed installations. Elastic Cloud managed service starts at $16.40 per month, with a free 14-day trial available.
SourceElasticsearch: Can I use Elasticsearch without Kibana?
Yes, Elasticsearch is a search engine independent of Kibana. Kibana is a visualization and analytics tool that works with Elasticsearch but is optional. You can use the Elasticsearch API directly for searching.
SourceElasticsearch: Does Elasticsearch support real-time indexing?
Elasticsearch indexes data with a refresh interval, typically 1 second. Data becomes searchable after the refresh cycle, making it near-real-time but not instantaneous. This can be configured but impacts performance.
SourceElasticsearch: What are Elasticsearch's scaling limitations?
Elasticsearch requires careful operational management at scale, including shard balancing, heap sizing, and monitoring. Large clusters can suffer from garbage collection issues and become expensive to operate.
SourceElasticsearch: Does Elasticsearch support transactions and rollbacks?
No, Elasticsearch does not support ACID transactions or rollbacks. Updates are expensive operations that delete and re-insert documents, making it unsuitable for transactional workloads.
SourceRelated pages
More on Elasticsearch
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