DBMS > GigaSpaces vs. H2 vs. HugeGraph vs. RocksDB vs. VictoriaMetrics

System Properties Comparison GigaSpaces vs. H2 vs. HugeGraph vs. RocksDB vs. VictoriaMetrics

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.

A fast-speed and highly-scalable Graph DBMS

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Graph DBMS
Search engine

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	0.13
Rank	#336	Overall
	#32	Graph DBMS

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

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

www.gigaspaces.com

www.h2database.com

github.com/hugegraph
hugegraph.apache.org

rocksdb.org

victoriametrics.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.h2database.com/html/main.html

hugegraph.apache.org/docs

github.com/facebook/rocksdb/wiki

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Gigaspaces Technologies

Thomas Mueller

Baidu

Facebook, Inc.

VictoriaMetrics

Initial release

2000

2005

2018

2013

2018

Current release

15.5, September 2020

2.2.220, July 2023

0.9

8.11.4, April 2024

v1.91, May 2023

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

Apache Version 2.0

Open Source

BSD

Open Source

Apache Version 2.0

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++

Server operating systems

Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux
macOS
Unix

Linux

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

schema-free

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

also supports composite index and range index

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

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

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

C++ API
Java API

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

.Net
C++
Java
Python
Scala

Java

Groovy
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

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

depending on used storage backend, e.g. Cassandra and HBase

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

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

Users, roles and permissions

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