How to Choose ParadeDB over MariaDB in PostgreSQL

Why should I choose ParadeDB over MariaDB for my next project?

ParadeDB extends PostgreSQL with native vector search, rich extensions, and modern analytics, making it a stronger choice than MariaDB for data-intensive apps.

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Description

Example H2

Example H3

Why pick ParadeDB instead of MariaDB?

ParadeDB inherits the full PostgreSQL feature set while adding native vector search, PostGIS, and JSONB improvements. MariaDB lacks built-in vector support and depends on plug-ins for GIS and JSON. ParadeDB therefore suits search, recommendation, and geo-aware ecommerce workloads without extra tooling.

Does ParadeDB scale horizontally?

Yes. ParadeDB’s extension compatibility keeps it eligible for Citus and other sharding layers, enabling partitioned tables and parallel query plans.MariaDB sharding relies on external proxies with limited planner awareness.

How does ParadeDB improve developer productivity?

Because ParadeDB speaks standard PostgreSQL, you keep psql, pgAdmin, and ORMs. MariaDB introduces MySQL-style quirks (e.g., LIMIT offset) that break PostgreSQL utilities. ParadeDB also supports extensions such as pgvector, pg_partman, and PostGIS—saving weeks of custom code.

Is SQL syntax different?

No. ParadeDB follows PostgreSQL 15 syntax exactly.Your existing queries and functions run unchanged, whereas MariaDB diverges on window functions, CTEs, and JSON operators.

How to migrate from MariaDB to ParadeDB?

1) Export data with mysqldump --tab or CSV. 2) Create matching tables in ParadeDB using standard PostgreSQL types. 3) Load data with COPY. 4) Rewrite MariaDB-specific SQL (e.g., IFNULL → COALESCE).5) Add ParadeDB extensions like CREATE EXTENSION pgvector;.

What performance gains can I expect?

Benchmarks show pgvector ANN search returning top-20 neighbors over 10 M products in <50 ms—an order of magnitude faster than MariaDB plus external search engines.

Best practices for ParadeDB adoption

Enable work_mem per connection for analytics, keep shared_buffers at 25% RAM, and create GIN indexes on JSONB for catalog filters. Use pgvector’s HNSW indexes on product embeddings.

Common mistakes and fixes

Missing extensions: Forgetting CREATE EXTENSION pgvector; causes unknown type errors.Fix: Install required extensions before loading data.

Using MySQL-style quotes: MariaDB’s backtick identifiers throw errors in ParadeDB. Fix: Switch to double quotes or lowercase identifiers.

Why How to Choose ParadeDB over MariaDB in PostgreSQL is important

How to Choose ParadeDB over MariaDB in PostgreSQL Example Usage


-- Find the top 3 products similar to a customer’s last purchase
WITH last_item AS (
    SELECT p.embedding
    FROM orders o
    JOIN orderitems oi ON oi.order_id = o.id
    JOIN products p ON p.id = oi.product_id
    WHERE o.customer_id = 42
    ORDER BY o.order_date DESC
    LIMIT 1
)
SELECT p.id, p.name, p.price
FROM products p, last_item l
ORDER BY p.embedding <-> l.embedding
LIMIT 3;

How to Choose ParadeDB over MariaDB in PostgreSQL Syntax


-- Connect to ParadeDB (PostgreSQL wire protocol)
psql "postgresql://user:pass@host:5432/ecommerce"

-- Enable vector search extension
CREATE EXTENSION IF NOT EXISTS pgvector;

-- Create a products table with an embedding column
CREATE TABLE products (
    id SERIAL PRIMARY KEY,
    name TEXT,
    price NUMERIC(10,2),
    stock INT,
    embedding VECTOR(384)
);

-- Build an HNSW index for fast ANN search
CREATE INDEX ON products USING hnsw (embedding vector_l2_ops) WITH (m = 16, ef_construction = 200);

-- Sample similarity query
SELECT id, name
FROM products
ORDER BY embedding <-> '[0.12,0.98, … ,0.34]'::vector
LIMIT 5;

Common Mistakes

Assuming MariaDB JSON equals PostgreSQL JSONB; JSON path queries and indexing differ. Use JSONB in ParadeDB and add a GIN index for speed.
Copy-pasting MariaDB backtick identifiers into ParadeDB, leading to syntax errors. Replace backticks with standard double quotes or omit quoting.