DBMS > Geode vs. GigaSpaces vs. HugeGraph vs. RocksDB vs. Sequoiadb

System Properties Comparison Geode vs. GigaSpaces vs. HugeGraph vs. RocksDB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

A fast-speed and highly-scalable Graph DBMS

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

NewSQL database with distributed OLTP and SQL

Primary database model

Key-value store

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS

Key-value store

Document store
Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

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

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

geode.apache.org

www.gigaspaces.com

github.com/hugegraph
hugegraph.apache.org

rocksdb.org

www.sequoiadb.com

Technical documentation

geode.apache.org/docs

docs.gigaspaces.com/latest/landing.html

hugegraph.apache.org/docs

github.com/facebook/rocksdb/wiki

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Gigaspaces Technologies

Baidu

Facebook, Inc.

Sequoiadb Ltd.

Initial release

2002

2000

2018

2013

Current release

1.1, February 2017

15.5, September 2020

0.9

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

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

Java, C++, .Net

Java

C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS
Solaris
Windows

Linux
macOS
Unix

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

yes

SQL

Support of SQL

SQL-like query language (OQL)

SQL-99 for query and DML statements

SQL-like query language

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

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

Java API
RESTful HTTP API
TinkerPop Gremlin

C++ API
Java API

proprietary protocol using JSON

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C++
Java
Python
Scala

Groovy
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

asynchronous Gremlin script jobs

JavaScript

Triggers

yes

Cache Event Listeners

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

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

yes

Source-replica 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

Eventual Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

yes, on a single node

ACID

yes

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

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

Access rights per client and object definable

Role-based access control

Users, roles and permissions

simple password-based access control

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