AkasicDB - 그래파이

Why a Single Engine Is All You Need for Complex AI Queries and Search

Storage architecture, query optimization, and vector search all work
together within a single engine.

1. Dual Storage: One Dataset, Two Storage Strategies

Data is stored in ways optimized for graph traversal and relational queries respectively, yet operates as a single logical DB. The same data is accessed via the fastest path depending on the purpose.
2. TJ Operator: Processing Relationship Traversal and Conditional Queries in One Step

Unlike conventional databases, AkasicDB unifies both operations into a single cost model using the Traversal-Join (TJ) operator. The bottleneck in AI response speed lies not in the model, but in the query executor.
3. A Structure Where Vector Search Operates Alongside Graph and SQL

Most vector DBs only perform standalone searches. In AkasicDB, vector search runs within a single query alongside graph traversal and SQL conditions. This is why it can deliver accurate answers even to complex questions.

A Unified Graph-Vector-Relational DBMS for Enterprise AI

One engine is all you need for AI data infrastructure. AkasicDB unifies vector, graph,
and relational DB into a single engine to maximize enterprise AI efficiency.

The more databases you operate separately, the more complex AI adoption becomes—and the less efficient.

The Inefficiency of Storing the Same Data Across Multiple DBs

A Structure That Requires Separate Execution of Relationship Traversal and Conditional Queries

The Dilemma Where Increasing Speed Reduces Accuracy and Operational Efficiency

AkasicDB overcomes the limitations of separated DB
stacks with a single unified engine.

If you are ready to fully leverage AI’s potential, explore adoption today.

Storage architecture, query optimization, and vector search all work
together within a single engine.

1. Dual Storage: One Dataset, Two Storage Strategies

2. TJ Operator: Processing Relationship Traversal and Conditional Queries in One Step

3. A Structure Where Vector Search Operates Alongside Graph and SQL

Vector · Graph · Relation—three types of queries, one engine.

No need to send vector, graph, and SQL queries separately and merge the results. AkasicDB automatically determines the optimal execution path within a single engine.

An Enterprise-Ready DBMS That Reliably Handles Large-Scale Data

Designed for real enterprise operations, not experimental environments. Performance remains stable even as data grows, with built-in security and access control.

The Core Engine of the Akasic Pipeline: AkasicDB

This is where data standardized by AkasicIN is stored, AkasicON policies are enforced, and AkasicAI queries are executed. A solid architecture ensures performance and stability across the entire pipeline.

GraphAI: A trusted AI data technology company across all industries.
GraphAI’s AI data solutions support fast and accurate enterprise decision-making.

The limitations of AI call for a fundamental
rethink—starting with the data architecture.

Build a fundamentally different AI data infrastructure within your enterprise with AkasicDB.

Interested in Adopting GraphAI Solutions?

그래파이 솔루션 도입을 희망하시나요?

A Unified Graph-Vector-Relational DBMS for Enterprise AI

One engine is all you need for AI data infrastructure. AkasicDB unifies vector, graph, and relational DB into a single engine to maximize enterprise AI efficiency.

The more databases you operate separately, the more complex AI adoption becomes—and the less efficient.

The Inefficiency of Storing the Same Data Across Multiple DBs

A Structure That Requires Separate Execution of Relationship Traversal and Conditional Queries

The Dilemma Where Increasing Speed Reduces Accuracy and Operational Efficiency

AkasicDB overcomes the limitations of separated DB stacks with a single unified engine.

If you are ready to fully leverage AI’s potential, explore adoption today.

Storage architecture, query optimization, and vector search all work together within a single engine.

1. Dual Storage: One Dataset, Two Storage Strategies

2. TJ Operator: Processing Relationship Traversal and Conditional Queries in One Step

3. A Structure Where Vector Search Operates Alongside Graph and SQL

Vector · Graph · Relation—three types of queries, one engine.

No need to send vector, graph, and SQL queries separately and merge the results. AkasicDB automatically determines the optimal execution path within a single engine.

An Enterprise-Ready DBMS That Reliably Handles Large-Scale Data

Designed for real enterprise operations, not experimental environments. Performance remains stable even as data grows, with built-in security and access control.

The Core Engine of the Akasic Pipeline: AkasicDB

This is where data standardized by AkasicIN is stored, AkasicON policies are enforced, and AkasicAI queries are executed. A solid architecture ensures performance and stability across the entire pipeline.

GraphAI: A trusted AI data technology company across all industries. GraphAI’s AI data solutions support fast and accurate enterprise decision-making.

The limitations of AI call for a fundamental rethink—starting with the data architecture.

Build a fundamentally different AI data infrastructure within your enterprise with AkasicDB.

Interested in Adopting GraphAI Solutions?

그래파이 솔루션 도입을 희망하시나요?

One engine is all you need for AI data infrastructure. AkasicDB unifies vector, graph,
and relational DB into a single engine to maximize enterprise AI efficiency.

AkasicDB overcomes the limitations of separated DB
stacks with a single unified engine.

Storage architecture, query optimization, and vector search all work
together within a single engine.

GraphAI: A trusted AI data technology company across all industries.
GraphAI’s AI data solutions support fast and accurate enterprise decision-making.

The limitations of AI call for a fundamental
rethink—starting with the data architecture.