DBMS > Drizzle vs. Elasticsearch vs. Ingres vs. Kinetica vs. Redis

System Properties Comparison Drizzle vs. Elasticsearch vs. Ingres vs. Kinetica vs. Redis

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Well established RDBMS

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	132.83
Rank	#7	Overall
	#1	Search engines

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

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

Website

www.elastic.co/elasticsearch

www.actian.com/databases/ingres

www.kinetica.com

redis.com
redis.io

Technical documentation

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

docs.actian.com/ingres

docs.kinetica.com

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

Developer

Drizzle project, originally started by Brian Aker

Elastic

Actian Corporation

Kinetica

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2008

2010

1974

originally developed at University Berkely in early 1970s

2012

2009

Current release

7.2.4, September 2012

8.6, January 2023

11.2, May 2022

7.1, August 2021

7.2.5, May 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Elastic License

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++

Java

C, C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

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

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

All search fields are automatically indexed

yes

with RediSearch module

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

SQL-like DML and DDL statements

with RediSQL module

APIs and other access methods

JDBC

Java API
RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

C
C++
Java
PHP

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

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

yes

user defined functions

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

Triggers

hooks for callbacks inside the server can be used.

yes

by using the 'percolation' feature

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

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Ingres Replicator

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

Eventual Consistency

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

Immediate 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

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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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