DBMS > Apache Druid vs. Axibase vs. mSQL vs. Oracle NoSQL vs. TimescaleDB

System Properties Comparison Apache Druid vs. Axibase vs. mSQL vs. Oracle NoSQL vs. TimescaleDB

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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

mSQL (Mini SQL) is a simple and lightweight RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Relational DBMS

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

druid.apache.org

axibase.com/docs/atsd/finance

hughestech.com.au/products/msql

www.oracle.com/database/nosql/technologies/nosql

www.timescale.com

Technical documentation

druid.apache.org/docs/latest/design

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.timescale.com

Developer

Apache Software Foundation and contributors

Axibase Corporation

Hughes Technologies

Oracle

Timescale

Initial release

2012

2013

1994

2011

2017

Current release

29.0.1, April 2024

15585

4.4, October 2021

23.3, December 2023

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free licenses can be provided

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache 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.

Implementation language

Java

Server operating systems

Linux
OS X
Unix

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Solaris SPARC/x86

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

optional

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

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like DML and DDL statements

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
PHP
Python
R
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

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

Sharding

none

Sharding

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

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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.

yes

off heap cache

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 and roles

fine grained access rights according to SQL-standard

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