DBMS > Apache Druid vs. Geode vs. Percona Server for MySQL vs. RocksDB

System Properties Comparison Apache Druid vs. Geode vs. Percona Server for MySQL vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

Key-value store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

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

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

druid.apache.org

geode.apache.org

www.percona.com/software/mysql-database/percona-server

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

geode.apache.org/docs

www.percona.com/downloads/Percona-Server-LATEST

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

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

Percona

Facebook, Inc.

Initial release

2012

2002

2008

2013

Current release

29.0.1, April 2024

1.1, February 2017

8.0.36-28, 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

GPL version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like query language (OQL)

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

Multi-source replication
Source-replica replication
XtraDB Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights per client and object definable

Users with fine-grained authorization concept

no user groups or roles

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