Databases · head to head
Elasticsearch vs PlanetScale

Elasticsearch
Databases
The heart of the Elastic Stack for search and analytics
- 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; PlanetScale pricing varies significantly across 17+ AWS and GCP regions
- They diverge on capability: Elasticsearch covers Full-text Search, PlanetScale covers Database Branching.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Elasticsearch and PlanetScale actually diverge.
| Attribute | Elasticsearch | PlanetScale |
|---|---|---|
| Pricing model | Unknown | usage-based |
| Platforms | Linux, Windows, macOS, Docker, Kubernetes | Cloud-hosted (AWS, GCP, Azure) |
| Founded | 2010 | 2018 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).
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 PlanetScale
- Database Branching
- Non-blocking Schema Changes
- Insights
- Horizontal Scaling
- Connection Pooling
- Query Caching
- Automatic Backups
- Global Replication
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Elasticsearch
- Real-time applicationsnot PlanetScale
- Content managementnot PlanetScale
- User profilesnot PlanetScale
- Mobile backendsnot PlanetScale
- Cachingnot PlanetScale
PlanetScale
- MySQL-compatible applications requiring horizontal scalingnot Elasticsearch
- PostgreSQL deployments with custom cluster configurationsnot Elasticsearch
- Multi-region database deployments on AWS or GCPnot Elasticsearch
- Applications requiring transparent sharding via Vitessnot 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
PlanetScale
- Pricing varies significantly across 17+ AWS and GCP regions
- Additional costs for EBS storage beyond base tier, backup storage, and egress
- Dedicated PgBouncer and replicas incur separate charges
- Metal tier pricing increases sharply with larger configurations
Pricing, plan by plan
Elasticsearch
Free- Self-ManagedFree
- Open source
- Self-hosted
- Elasticsearch Cloud$16.4/month
- Managed service
- 14-day free trial
PlanetScale
Free- Postgres EBS Single-Node (ARM64 PS-5)$5/month
- 512 MiB RAM
- Single-node configuration
- EBS storage included
- Postgres EBS HA (ARM64 PS-5)$15/month
- 512 MiB RAM
- 3-node high-availability setup
- 1 primary + 2 replicas
- Postgres Metal (M-10)$50/month
- 1/8 vCPU, 1 GiB RAM
- 3-node HA configuration
- 10 GiB NVMe storage included
- Vitess Non-Metal 3-Node$39/month
- Sharding-capable database
- x86-64 architecture
- 3-node configuration
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 PlanetScale if
- You need database branching.
- You want to start without paying.
- You work on Cloud-hosted (AWS, GCP, Azure).
- You also want non-blocking schema changes.
Questions people ask
- Is Elasticsearch or PlanetScale better?
- Neither clearly leads. Elasticsearch starts at Free and PlanetScale at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Elasticsearch or PlanetScale?
- Elasticsearch starts at Free and PlanetScale at Free.
- Does Elasticsearch or PlanetScale run on more platforms?
- Elasticsearch runs on Linux, Windows, macOS, Docker, Kubernetes. PlanetScale runs on Cloud-hosted (AWS, GCP, Azure).
- 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 PlanetScale is typically brought in for.
- What can Elasticsearch do that PlanetScale cannot?
- Elasticsearch covers Full-text Search, Real-time Analytics, Distributed Architecture, RESTful API. PlanetScale covers Database Branching, Non-blocking Schema Changes, Insights, Horizontal Scaling. Both handle Web 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.
SourcePlanetScale: How much does a PlanetScale Postgres database cost per month?
PlanetScale Postgres pricing starts at $5/month for single-node ARM64 configurations with 512 MiB RAM and $15/month for the same specs in high-availability mode with 1 primary and 2 replicas. Metal tier starts at $50/month for M-10 configuration (1/8 vCPU, 1 GiB RAM). Exact pricing depends on cluster size, node architecture (ARM64 vs x86-64), storage configuration, and selected AWS/GCP region.
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.
SourcePlanetScale: Is there a free tier for PlanetScale?
PlanetScale offers a free tier for development and testing workloads. After free tier limits are reached, usage-based pricing applies starting at $5/month for the smallest Postgres single-node configuration, with costs scaling based on cluster size, compute, storage, and additional features like dedicated PgBouncer or replicas.
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.
SourcePlanetScale: What is the difference between PlanetScale ARM64 and x86-64 pricing?
ARM64 instances cost significantly less than x86-64 equivalents. For example, a Postgres EBS HA cluster with 512 MiB RAM costs $15/month on ARM64 but $39/month on x86-64. This pricing difference extends across all cluster sizes, with larger x86-64 configurations reaching up to $5,599/month compared to ARM64 alternatives.
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.
SourcePlanetScale: What is included in a PlanetScale cluster price versus additional costs?
The advertised cluster price covers the base compute and configured storage. Additional charges apply for EBS storage beyond the base allocation, backup storage, data egress, optional dedicated PgBouncer connections, and replicas beyond the base high-availability configuration. Regional pricing varies across 17+ AWS and GCP zones.
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
More on PlanetScale
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- PlanetScale vs BigQuery
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- PlanetScale vs IBM Db2
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