DBMS > GridDB vs. InfluxDB vs. MySQL vs. openGauss vs. Redis

System Properties Comparison GridDB vs. InfluxDB vs. MySQL vs. openGauss vs. Redis

Editorial information provided by DB-Engines

Name

Description

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

DBMS for storing time series, events and metrics

Widely used open source RDBMS

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Key-value store

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

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS

with GEO package

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	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

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

Website

griddb.net

www.influxdata.com/products/influxdb-overview

www.mysql.com

gitee.com/opengauss
opengauss.org

redis.com
redis.io

Technical documentation

docs.griddb.net

docs.influxdata.com/influxdb

dev.mysql.com/doc

docs.opengauss.org/en
gitee.com/opengauss/docs

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

Developer

Toshiba Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Huawei and openGauss community

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2013

1995

2019

2009

Current release

5.1, August 2022

2.7.6, April 2024

8.4.0, April 2024

3.0, March 2022

7.2.5, May 2024

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

MIT-License; commercial enterprise version available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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 MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

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

Implementation language

C++

C and C++

C, C++, Java

Server operating systems

Linux

Linux
OS X

through Homebrew

FreeBSD
Linux
OS X
Solaris
Windows

Linux

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

Numeric data and Strings

yes

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.

yes

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

yes

with proprietary extensions

ANSI SQL 2011

with RediSQL module

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP API
JSON over UDP

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

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

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java

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

proprietary syntax

yes

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

Sharding

in enterprise version only

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning (by range, list and hash)

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID at container level

ACID

not for MyISAM storage engine

ACID

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Depending on used storage engine

yes

User concepts

Access control

Access rights for users can be defined per database

simple rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

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

More information provided by the system vendor

Specific characteristics

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

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

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

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

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

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

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

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

GitHub trending repository
» more

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

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

Open source core with closed source clustering available either on-premise or on...
» more

News

Deadman Alerts with Grafana and InfluxDB Cloud 3.0
20 June 2024

Chasing the Skies: Monitoring Flights with InfluxDB
4 June 2024

Monitoring Your Cloud Environments and Applications with InfluxDB
30 May 2024

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 May 2024

Using Parquet’s Bloom Filters
28 May 2024

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