DBMS > Apache Druid vs. TimescaleDB

System Properties Comparison Apache Druid vs. TimescaleDB

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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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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Trend Chart

Score	2.63
Rank	#101	Overall
	#50	Relational DBMS
	#7	Time Series DBMS

Score	2.77
Rank	#97	Overall
	#5	Time Series DBMS

Website

druid.apache.org

www.timescale.com

Technical documentation

druid.apache.org/docs/latest/design

docs.timescale.com

Developer

Apache Software Foundation and contributors

Timescale

Initial release

2012

2017

Current release

0.20.2, March 2021

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Timescale is the creator of TimescaleDB , the first open-source relational database...
» more

Competitive advantages

TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more

Typical application scenarios

DevOps and Infrastructure Monitoring All monitoring data is time-series data. Efficiently...
» more

Key customers

TransferWise, Maersk, AppDynamics, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco,...
» more

Market metrics

With over 9,000 GitHub stars and growing, 600,000 active databases, and an active...
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Licensing and pricing models

TimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*,...
» more

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