DBMS > AllegroGraph vs. ArangoDB vs. GridDB vs. Redis vs. STSdb

System Properties Comparison AllegroGraph vs. ArangoDB vs. GridDB vs. Redis vs. STSdb

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.

Scalable in-memory time series database optimized for IoT and Big Data

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.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Graph DBMS
Key-value store
Search engine

Time Series DBMS

Key-value store

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

Key-value store

Secondary database models

Spatial DBMS

Key-value store
Relational 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	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	3.32
Rank	#90	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores
	#10	Search engines

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

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

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

docs.arangodb.com

docs.griddb.net

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

Social network pages

Developer

Franz Inc.

ArangoDB Inc.

Toshiba Corporation

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

STS Soft SC

Initial release

2004

2012

2013

2009

2011

Current release

8.0, December 2023

3.11.5, November 2023

5.1, August 2022

7.2.4, January 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2; Commercial license (Enterprise) available

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

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

Open Source

GPLv2, commercial license available

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.

ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.

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

Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Windows

Data scheme

yes

RDF schemas

schema-free

automatically recognizes schema within a collection

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, double, boolean, list, hash

yes

numerical, string, blob, geometry, boolean, timestamp

partial

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

yes

primitive types and user defined types (classes)

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.

bulk load of XML files possible

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SPARQL is used as query language

SQL92, SQL-like TQL (Toshiba Query Language)

with RediSQL module

APIs and other access methods

RESTful HTTP API
SPARQL

AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

proprietary protocol

RESP - REdis Serialization Protocol

.NET Client API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust

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

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#
Java

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

JavaScript

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

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

since version 2.0

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

Source-replica replication with configurable replication factor

Source-replica replication

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be done with stored procedures in JavaScript

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

configurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)

Immediate consistency within container, eventual consistency across containers

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

relationships in graphs

Transaction concepts

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

ACID

ACID at container level

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

Access rights for users can be defined per database

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

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

Consolidation: As a native multi-model database, can be used as a full blown document...
» more

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Native multi-model in ArangoDB is being used for a broad range of projects across...
» more

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

ArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more

GitHub trending repository
» more

Licensing and pricing models

Very permissive Apache 2 License for Community Edition & commercial licenses are...
» more

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.