DBMS > Ehcache vs. Redis vs. StarRocks

System Properties Comparison Ehcache vs. Redis vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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.

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Key-value store

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

Relational DBMS

Secondary database models

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	4.89
Rank	#67	Overall
	#8	Key-value stores

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

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

www.ehcache.org

redis.com
redis.io

www.starrocks.io

Technical documentation

www.ehcache.org/documentation

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

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Terracotta Inc, owned by Software AG

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

The Linux Foundation

since Feb 2023

Initial release

2009

2020

Current release

3.10.0, March 2022

7.2.5, May 2024

2.5.3, March 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Open Source

Apache Version 2.0

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

Java

C++, Java

Server operating systems

All OS with a Java VM

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

schema-free

yes

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

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.

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

with RediSQL module

yes

APIs and other access methods

JCache

proprietary protocol

RESP - REdis Serialization Protocol

JDBC
MySQL protocol

Supported programming languages

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

Java

Server-side scripts

Stored procedures

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

user defined functions

Triggers

yes

Cache Event Listeners

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

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

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

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

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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 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

Role based access control and fine grained access rights

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