PostgreSQL with Columnar Storage
Scaled Infinitely
Transactions, analytics, AI — all in one place, all working in tandem.
Authoritative. Across all data types.
Pushing the physical limits of consistency, latency, and performance.
Build intelligent systems with Tacnode today. For your future.
A True Unification of Data Management Systems
No more data silos, architectural complexities, unpredictable latencies and unavoidable inconsistencies.
Relational Database
Retain the familiarity of PostgreSQL.
NoSQL Database
JSON support.
Horizontal scaling.
Agile development.
Horizontal scaling.
Agile development.
Search Engine
Real-time.
Structured search.
Semantic search.
Structured search.
Semantic search.
Data Lakehouse
Real-time.
Consistent.
Performant.
Consistent.
Performant.
Cloud Agnostic
One click away from every major cloud service provider.
Fully Managed
Instant elasticity.
Maintenance-free.
Intuitive monitoring.
Maintenance-free.
Intuitive monitoring.
PostgreSQL
Compatible
Documentation. Tools. Frameworks.
Stick with the ecosystem you know and love.
Innovative does not have to be disruptive.
A Better Lakehouse
Stand out with real-time analytics — unmatched performance, strong consistency, zero data latency.
User Retention Analysis
A leading digital advertising SaaS platform
8x
Average performance improvement
Sales and ERP Data Analysis
A trending global e-commerce group
100x / 9x
Max / Avg query time reduction
IoT Data Processing and Analysis
A global communication services conglomerate
9x / 4x
Throughput improvement / Cost reduction
A Better Database
Better Relational. Better NoSQL.
Single Point Of Truth
One home to all data your applications will ever need:
StructuredSemi-structuredUnstructuredAlways consistentAlways in real timeAlways authoritativeUnlimited scalabilityHigh availability and reliabilityCentralized management
Bring AI to Your Data
Extract knowledge to discover insights.
By training/feeding AI with your private data:
Fine-tuning/Retrieval-Augmented Generation (RAG).
Make real-time predictions and decisions.
Use cases:
By training/feeding AI with your private data:
Fine-tuning/Retrieval-Augmented Generation (RAG).
Make real-time predictions and decisions.
Use cases:
Knowledge baseIntelligent recommendationsOmni search
create-embeddings.sql
insert.sql
CREATE TABLE embeddings ( id SERIAL PRIMARY KEY, text VARCHAR(255) NOT NULL, embedding VECTOR(768) NOT NULL, create_date DATE DEFAULT CURRENT_DATE);
INSERT INTO embeddings (text, embedding) VALUES ('This is a sample text.', '[0.1, 0.2, ..., 0.768]'),('Another example text.', '[0.3, 0.4, ..., 0.768]'),
SELECT * FROM embeddings;
id | text | embedding | create_date----+------------------------+------------------------+------------- 1 | This is a sample text. | [0.1, 0.2, ..., 0.768] | 2023-08-22 2 | Another example text. | [0.3, 0.4, ..., 0.768] | 2023-08-22(3 rows)