DBMS > GridDB vs. Redis vs. Riak KV vs. RRDtool vs. Stardog

System Properties Comparison GridDB vs. Redis vs. Riak KV vs. RRDtool vs. Stardog

Editorial information provided by DB-Engines

Name

Description

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.

Distributed, fault tolerant key-value store

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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

Primary database model

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

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

Graph DBMS
RDF store

Secondary database models

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	1.95
Rank	#128	Overall
	#10	Time Series DBMS

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

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

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

Website

griddb.net

redis.com
redis.io

oss.oetiker.ch/rrdtool

www.stardog.com

Technical documentation

docs.griddb.net

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

www.tiot.jp/riak-docs/riak/kv/latest

oss.oetiker.ch/rrdtool/doc

docs.stardog.com

Developer

Toshiba Corporation

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

OpenSource, formerly Basho Technologies

Tobias Oetiker

Stardog-Union

Initial release

2013

2009

1999

2010

Current release

5.1, August 2022

7.2.4, January 2024

3.2.0, December 2022

1.8.0, 2022

7.3.0, May 2020

License

Commercial or Open Source

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

Apache version 2, commercial enterprise edition

Open Source

GPL V2 and FLOSS

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++

Erlang

Implementations in Java (e.g. RRD4J) and C# available

Java

Server operating systems

Linux

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
OS X

HP-UX
Linux

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

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

Numeric data only

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.

Exporting into and restoring from XML files possible

Import/export of XML data possible

Secondary indexes

yes

with RediSearch module

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

with RediSQL module

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

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

proprietary protocol

RESP - REdis Serialization Protocol

HTTP API
Native Erlang Interface

in-process shared library
Pipes

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++
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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

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

Erlang

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

yes

pre-commit hooks and post-commit hooks

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

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

selectable replication factor

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

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

through RedisGears

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency

none

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

links between data sets can be stored

yes

relationships in graphs

Transaction concepts

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

ACID at container level

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

by using the rrdcached daemon

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

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

yes, using Riak Security

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
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Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
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Market metrics

GitHub trending repository
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Licensing and pricing models

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