DBMS > GridDB vs. HBase vs. InfluxDB vs. Oracle NoSQL vs. Redis

System Properties Comparison GridDB vs. HBase vs. InfluxDB vs. Oracle NoSQL vs. Redis

Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

DBMS for storing time series, events and metrics

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Wide column store

Time Series DBMS

Document store
Key-value store
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

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	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

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

Website

griddb.net

hbase.apache.org

www.influxdata.com/products/influxdb-overview

www.oracle.com/database/nosql/technologies/nosql

redis.com
redis.io

Technical documentation

docs.griddb.net

hbase.apache.org/book.html

docs.influxdata.com/influxdb

docs.oracle.com/en/database/other-databases/nosql-database/index.html

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

Developer

Toshiba Corporation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2013

2008

2013

2011

2009

Current release

5.1, August 2022

2.3.4, January 2021

2.7.6, April 2024

23.3, December 2023

7.2.4, January 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

Apache version 2

Open Source

MIT-License; commercial enterprise version available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Implementation language

C++

Java

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux
OS X

through Homebrew

Linux
Solaris SPARC/x86

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

yes

schema-free, schema definition possible

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

options to bring your own types, AVRO

Numeric data and Strings

optional

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.

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

SQL-like DML and DDL statements

with RediSQL module

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Java API
RESTful HTTP API
Thrift

HTTP API
JSON over UDP

RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C
C#
Go
Java
JavaScript (Node.js)
Python

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

Coprocessors in Java

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

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

Multi-source replication
Source-replica replication

selectable replication factor

in enterprise version only

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

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

yes

with Hadoop integration

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

Transaction concepts

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

ACID at container level

Single row ACID (across millions of columns)

configurable

ACID within a storage node (=shard)

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

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

off heap cache

yes

User concepts

Access control

Access rights for users can be defined per database

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

simple rights management via user accounts

Access rights for users and roles

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...
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InfluxData is the creator of InfluxDB , the open source time series database. It...
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Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Time to Value InfluxDB is available in all the popular languages and frameworks,...
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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...
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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,...
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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

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30 April 2024

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26 April 2024

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8 April 2024

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