DBMS > GigaSpaces vs. Greenplum vs. InfinityDB vs. IRONdb vs. Redis

System Properties Comparison GigaSpaces vs. Greenplum vs. InfinityDB vs. IRONdb vs. Redis

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Website

www.gigaspaces.com

greenplum.org

boilerbay.com

www.circonus.com/solutions/time-series-database/

redis.com
redis.io

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.greenplum.org

boilerbay.com/infinitydb/manual

docs.circonus.com/irondb/category/getting-started

docs.redis.com/latest/index.html
redis.io/docs

Developer

Gigaspaces Technologies

Pivotal Software Inc.

Boiler Bay Inc.

Circonus LLC.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2000

2005

2002

2017

2009

Current release

15.5, September 2020

7.0.0, September 2023

4.0

V0.10.20, January 2018

7.2.5, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

commercial

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Java, C++, .Net

Java

C and C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux

All OS with a Java VM

Linux

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

yes

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

yes

text, numeric, histograms

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

yes

since Version 4.2

Secondary indexes

yes

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

yes

with RediSearch module

SQL

Support of SQL

SQL-99 for query and DML statements

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

with RediSQL module

APIs and other access methods

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

JDBC
ODBC

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

HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

.Net
C++
Java
Python
Scala

C
Java
Perl
Python
R

Java

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

yes, in Lua

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes, event driven architecture

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic, metric affinity per node

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

none

configurable replication factor, datacenter aware

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

through RedisGears

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 per node, eventual consistency across nodes

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

yes

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

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

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