DBMS > GigaSpaces vs. H2 vs. RocksDB vs. TypeDB vs. Vitess

System Properties Comparison GigaSpaces vs. H2 vs. RocksDB vs. TypeDB vs. Vitess

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key-value store

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.

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

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

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.h2database.com/html/main.html

github.com/facebook/rocksdb/wiki

typedb.com/docs

vitess.io/docs

Developer

Gigaspaces Technologies

Thomas Mueller

Facebook, Inc.

Vaticle

The Linux Foundation, PlanetScale

Initial release

2000

2005

2013

2016

2013

Current release

15.5, September 2020

2.2.220, July 2023

8.11.4, April 2024

2.26.3, January 2024

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD

Open Source

GPL Version 3, commercial licenses available

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

Java

C++

Java

Server operating systems

Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

with proprietary extensions

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC

C++ API
Java API

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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

Java

C
C++
Go
Java
Perl
Python
Ruby

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

by using Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Multi-source replication

by using Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

substituted by the relationship feature

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

yes

at REST API level; other APIs in progress

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

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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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