How to Choose ParadeDB Over Redshift in PostgreSQL

Why pick ParadeDB instead of Redshift?

ParadeDB lives inside PostgreSQL, so you avoid duplicating data into a separate Redshift warehouse. Fewer copies cut storage bills and simplify security audits.

Because ParadeDB runs where your OLTP data already resides, analysts query fresh data instantly—no nightly ETLs or stale dashboards.

ParadeDB uses PostgreSQL’s executor but adds columnar storage and vector indexes. This shrinks scan times dramatically compared with Redshift’s distributed row model on small to mid-size datasets.

Redshift pricing scales by node‐hours.ParadeDB is just a free open-source extension; you pay only for the PostgreSQL compute you already use.

Developers keep a single toolchain—pg_dump, logical replication, psql—rather than juggling Redshift-specific syntax and drivers.

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How do I install ParadeDB?

Install the extension with a single command once you’ve added the package repository to your server:

CREATE EXTENSION paradedb CASCADE;

The CASCADE clause installs required sub-extensions like pgvector automatically.

What is the basic ParadeDB syntax?

After installation, create columnar or vector-optimized tables using the USING paradedb clause:

CREATE TABLE Orders_analytic
(
id BIGINT,
customer_id BIGINT,
order_date DATE,
total_amount NUMERIC
) USING paradedb.columnar;

The underlying rows stay queryable with standard SQL while ParadeDB handles compression and vectorization.

Can ParadeDB power product recommendations?

Yes. Combine ParadeDB with pgvector to store product embeddings and run fast similarity search directly in Postgres.

-- Create vector column
ALTER TABLE Products ADD COLUMN embedding vector(384);

-- Build ParadeDB vector index
CREATE INDEX ON Products USING paradedb.ivfflat (embedding);

-- Query for similar products
SELECT id, name
FROM Products
ORDER BY embedding <-> (SELECT embedding FROM Products WHERE id = 42)
LIMIT 5;

This avoids exporting embeddings to an external ML service or Redshift ML.

How does query performance compare?

On datasets under 2 TB—a sweet spot for most Series B SaaS companies—benchmarks show ParadeDB responsive in milliseconds where single-node Redshift clusters take seconds due to network shuffling.

What are best practices?

1. Isolate analytics tables in a separate schema to keep OLTP catalogs uncluttered.
2. Use paradedb.columnar for wide fact tables; use paradedb.ivfflat for vector search.
3. Replicate to read-only replicas for heavy BI workloads.

Common Mistake #1 – Forgetting to ANALYZE

Skipping ANALYZE after bulk loads leads Postgres to misestimate row counts and pick slow plans. Run ANALYZE or enable autovacuum.

Common Mistake #2 – Using SERIAL in Columnar Tables

SERIAL forces row-by-row inserts. Prefer BIGINT GENERATED BY DEFAULT AS IDENTITY to batch-friendly writes.

FAQ

Does ParadeDB work on Amazon RDS?

No. RDS blocks custom extensions. Use self-hosted Postgres on EC2 or Aurora PostgreSQL compatible versions that permit shared libraries.

Can I mix ParadeDB and regular tables?

Absolutely. ParadeDB tables live beside classic tables. Joins work normally, and you can migrate incrementally.

Is ParadeDB production-ready?

Yes. Companies like Airbyte and Supabase use it in production for real-time analytics at multi-terabyte scale.