DBMS > Kinetica vs. SAP HANA vs. Titan vs. TypeDB

System Properties Comparison Kinetica vs. SAP HANA vs. Titan vs. TypeDB

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Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Fully vectorized database across both GPUs and CPUs

In-memory, column based data store. Available as appliance or cloud service

Titan is a Graph DBMS optimized for distributed clusters.

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Relational DBMS

Graph DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

www.kinetica.com

www.sap.com/products/hana.html

github.com/thinkaurelius/titan

typedb.com

Technical documentation

docs.kinetica.com

help.sap.com/hana

github.com/thinkaurelius/titan/wiki

typedb.com/docs

Developer

Kinetica

SAP

Aurelius, owned by DataStax

Vaticle

Initial release

2012

2010

2012

2016

Current release

7.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache license, version 2.0

Open Source

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java

Server operating systems

Linux

Appliance or cloud-service

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

via pluggable storage backends

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

substituted by the relationship feature

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

yes

User authentification and security via Rexster Graph Server

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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