DBMS > Apache Druid vs. FileMaker vs. PouchDB vs. RocksDB vs. VoltDB

System Properties Comparison Apache Druid vs. FileMaker vs. PouchDB vs. RocksDB vs. VoltDB

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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

JavaScript DBMS with an API inspired by CouchDB

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS
Time Series DBMS

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Trend Chart

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

druid.apache.org

www.claris.com/filemaker

pouchdb.com

rocksdb.org

www.voltdb.com

Technical documentation

druid.apache.org/docs/latest/design

www.claris.com/resources/documentation

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

docs.voltdb.com

Developer

Apache Software Foundation and contributors

Claris

a subsidiary of Apple

Apache Software Foundation

Facebook, Inc.

VoltDB Inc.

Initial release

2012

1983

2012

2013

2010

Current release

29.0.1, April 2024

19.4.1, November 2021

7.1.1, June 2019

9.2.1, May 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

BSD

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

C++

Java, C++

Server operating systems

Linux
OS X
Unix

iOS

client part only
Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Linux
OS X

for development

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

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

A http query request can return the data in XML format

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL for querying

yes

via plugins

yes

only a subset of SQL 99

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Filemaker WebDirect
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

PHP

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication, warm standby

since Version 14

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

Snapshots and command logging

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

simple rights management via user accounts and connection to external directory services

Users and roles with access to stored procedures

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