DBMS > GigaSpaces vs. Machbase Neo vs. OceanBase vs. Redis vs. SiriDB

System Properties Comparison GigaSpaces vs. Machbase Neo vs. OceanBase vs. Redis vs. SiriDB

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

TimeSeries DBMS for AIoT and BigData

A distributed, high available RDBMS compatible with Oracle and MySQL

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.

Open Source Time Series DBMS

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Relational DBMS

Key-value store

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

Time Series DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Wide column store

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	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

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

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

machbase.com/dbms

en.oceanbase.com/docs/oceanbase-database

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

docs.siridb.com

Developer

Gigaspaces Technologies

Machbase

OceanBase

previously Alibaba and Ant Group

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Cesbit

Initial release

2000

2013

2010

2009

2017

Current release

15.5, September 2020

V8.0, August 2023

4.3.0, April 2024

7.2.5, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

free test version available

Open Source

Commercial license available

Open Source

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

Open Source

MIT License

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

C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux
macOS
Windows

Linux

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

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

yes

Numeric data

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

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

yes

with RediSQL module

APIs and other access methods

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

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

proprietary protocol

RESP - REdis Serialization Protocol

HTTP API

Supported programming languages

.Net
C++
Java
Python
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

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

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

Multi-source replication using Paxos

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

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

Transaction concepts

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

ACID

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

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

volatile and lookup table

yes

User concepts

Access control

Role-based access control

simple password-based access control

Access rights for users, groups and roles 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

simple rights management via user accounts

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