DBMS > Cubrid vs. Elasticsearch vs. Geode vs. Kinetica vs. Redis

System Properties Comparison Cubrid vs. Elasticsearch vs. Geode vs. Kinetica vs. Redis

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Fully vectorized database across both GPUs and CPUs

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

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

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS
Time Series 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	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

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

Website

cubrid.com (korean)
cubrid.org (english)

www.elastic.co/elasticsearch

geode.apache.org

www.kinetica.com

redis.com
redis.io

Technical documentation

cubrid.org/manuals

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

geode.apache.org/docs

docs.kinetica.com

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

Developer

CUBRID Corporation, CUBRID Foundation

Elastic

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Kinetica

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2008

2010

2002

2012

2009

Current release

11.0, January 2021

8.6, January 2023

1.1, February 2017

7.1, August 2021

7.2.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Elastic License

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

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, C++, Java

Java

C, C++

Server operating systems

Linux
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

schema-free

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

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

All search fields are automatically indexed

yes

with RediSearch module

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language (OQL)

SQL-like DML and DDL statements

with RediSQL module

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

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

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
All JVM based languages
C++
Groovy
Java
Scala

C++
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

Java Stored Procedures

yes

user defined functions

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

Triggers

yes

by using the 'percolation' feature

yes

Cache Event Listeners

yes

triggers when inserted values for one or more columns fall within a specified range

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

none

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

yes

Multi-source 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

ES-Hadoop Connector

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Immediate Consistency or Eventual 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

yes

Transaction concepts

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

ACID

yes, on a single node

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.

Memcached and Redis integration

yes

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights per client and object definable

Access rights for users and roles on table level

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

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