DBMS > Drizzle vs. GigaSpaces vs. OrientDB vs. Redis vs. Stardog

System Properties Comparison Drizzle vs. GigaSpaces vs. OrientDB vs. Redis vs. Stardog

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Multi-model DBMS (Document, Graph, Key/Value)

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.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Document store
Graph DBMS
Key-value store

Key-value store

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

Graph DBMS
RDF store

Secondary database models

Graph DBMS
Search engine

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.orientdb.com/docs/last/index.html

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

docs.stardog.com

Developer

Drizzle project, originally started by Brian Aker

Gigaspaces Technologies

OrientDB LTD; CallidusCloud; SAP

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Stardog-Union

Initial release

2008

2000

2010

2009

2010

Current release

7.2.4, September 2012

15.5, September 2020

3.2.29, March 2024

7.2.4, January 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache version 2

Open Source

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

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C++

Java, C++, .Net

Java

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
macOS
Windows

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

schema-free and OWL/RDFS-schema support

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

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

Import/export of XML data possible

Secondary indexes

yes

with RediSearch module

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

with proprietary extensions

SQL-99 for query and DML statements

SQL-like query language, no joins

with RediSQL module

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

proprietary protocol

RESP - REdis Serialization Protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C
C++
Java
PHP

.Net
C++
Java
Python
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Java, Javascript

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

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

hooks for callbacks inside the server can be used.

yes, event driven architecture

Hooks

publish/subscribe channels provide some trigger functionality; RedisGears

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

could be achieved with distributed queries

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationship in graphs

yes

relationships in graphs

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

ACID

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

Access rights for users and roles; record level security configurable

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

Access rights for users and roles

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