DBMS > GigaSpaces vs. InfinityDB vs. Memcached vs. RocksDB vs. SQream DB

System Properties Comparison GigaSpaces vs. InfinityDB vs. Memcached vs. RocksDB vs. SQream DB

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

A Java embedded Key-Value Store which extends the Java Map interface

In-memory key-value store, originally intended for caching

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

boilerbay.com/infinitydb/manual

github.com/memcached/memcached/wiki

github.com/facebook/rocksdb/wiki

docs.sqream.com

Developer

Gigaspaces Technologies

Boiler Bay Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Facebook, Inc.

SQream Technologies

Initial release

2000

2002

2003

2013

2017

Current release

15.5, September 2020

4.0

1.6.25, March 2024

8.11.4, April 2024

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

BSD license

Open Source

BSD

commercial

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++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
macOS
Solaris
Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes, ANSI Standard SQL Types

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

manual creation possible, using inversions based on multi-value capability

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

C++ API
Java API

.Net
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

Java

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions in Python

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

Repcached, a Memcached patch, provides this functionallity

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

yes

ACID

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

Role-based access control

yes

using SASL (Simple Authentication and Security Layer) protocol

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