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Feldera vs pg_ivm

Feldera: An incremental SQL engine grounded in DBSP theory that updates any SQL query from changes only. pg_ivm: A Postgres extension that keeps materialized views updated incrementally inside the same transaction.

key differences

  • Feldera is built for larger datasets (≤ 10 TB) than pg_ivm (≤ 100 GB).
  • Horizontal scaling is native in Feldera and none in pg_ivm.
  • Transactions: Feldera offers limited ACID; pg_ivm offers full.
  • Only Feldera has json, change data capture, streaming ingest.
  • Only pg_ivm has transactions, triggers.

choose feldera for

  • +Incremental computation of complex analytics over changing data
  • +Real-time feature engineering
  • +Streaming ETL into Delta Lake or Iceberg

best at · Streaming, Real-time analytics, Feature store

choose pg-ivm for

  • +Always-fresh summary tables for dashboards
  • +Replacing periodic REFRESH MATERIALIZED VIEW jobs

best at · Real-time analytics, OLTP

FelderaAn incremental SQL engine grounded in DBSP theory that updates any SQL query from changes only.
pg_ivmA Postgres extension that keeps materialized views updated incrementally inside the same transaction.
overview
Primary model
Relational
Relational
Also supports
–
–
Type
Database engine
Extension
Status
Active
Active
Developer
Feldera, Inc.
SRA OSS (IVM Development Group)
First release
2023
2022
Latest version
0.369.0 (Oct 23, 2026)
1.17 (Oct 18, 2026)
License
Open source (permissive)MIT (open-source edition); Enterprise is commercial
Open source (permissive)PostgreSQL License
Free tier
✓
✓
popularity
WhichDB Score
15.8
6.4
Rank
#202
#363
GitHub stars
2.1K
1.5K
Stack Overflow questions
–
–
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Small (≤ 100 GB)
Horizontal scaling
Native
None
Multi-region
None
None
ACID
Limited
Full
Consistency
Strong
Strong
Schema
Strict
Strict
Architecture
Single node, Distributed, Client server
Single node, Primary replica, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
✓
—
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
AWS
–
capabilities
Transactions
—
✓
Joins
✓
✓
Secondary indexes
—
—
Full-text search
—
—
Vector search
—
—
Geospatial
—
—
JSON
✓
—
Change data capture
✓
—
Triggers
—
✓
Stored procedures
—
—
Materialized views
✓
✓
TTL / expiry
—
—
Pub/Sub
—
—
Columnar storage
—
—
In-memory
—
—
Durable persistence
✓
✓
Compression
—
—
Encryption at rest
—
—
Role-based access
—
—
Time travel
—
—
Branching
—
—
Online schema changes
—
—
Streaming ingest
✓
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
SQL (Apache Calcite dialect)
SQL
Client languages
Python, Rust
Any Postgres driver
Best for
Streaming, Real-time analytics, Feature store, Lakehouse
Real-time analytics, OLTP
Add more to this comparisonNot sure either fits? Try smart match

Feldera vs pg_ivm: FAQ

What is the difference between Feldera and pg_ivm?

Feldera: An incremental SQL engine grounded in DBSP theory that updates any SQL query from changes only. pg_ivm: A Postgres extension that keeps materialized views updated incrementally inside the same transaction. Feldera is built for larger datasets (≤ 10 TB) than pg_ivm (≤ 100 GB). Horizontal scaling is native in Feldera and none in pg_ivm. Transactions: Feldera offers limited ACID; pg_ivm offers full.

When should I choose Feldera over pg_ivm?

Choose Feldera for incremental computation of complex analytics over changing data, real-time feature engineering and streaming ETL into Delta Lake or Iceberg. Choose pg_ivm for always-fresh summary tables for dashboards and replacing periodic REFRESH MATERIALIZED VIEW jobs.

Is Feldera or pg_ivm more popular?

Feldera ranks #202 on the WhichDB Score (15.8/100) and pg_ivm ranks #363 (6.4/100). Popularity is not fit: check the requirements that matter for your project.

Are Feldera and pg_ivm open source?

Yes. Feldera is open source. License: MIT (open-source edition); Enterprise is commercial. Yes. pg_ivm is open source. License: PostgreSQL License.