DBMS > Apache Druid vs. Apache Impala vs. Drizzle vs. RDF4J vs. Sequoiadb

System Properties Comparison Apache Druid vs. Apache Impala vs. Drizzle vs. RDF4J vs. Sequoiadb

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

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

Analytic DBMS for Hadoop

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

RDF store

Document store
Relational DBMS

Secondary database models

Document 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	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

impala.apache.org/impala-docs.html

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Sequoiadb Ltd.

Initial release

2012

2013

2008

2004

2013

Current release

29.0.1, April 2024

4.1.0, June 2022

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

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++

Java

C++

Server operating systems

Linux
OS X
Unix

Linux

FreeBSD
Linux
OS X

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC

C
C++
Java
PHP

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

JavaScript

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control

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More resources

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