DBMS > Apache Druid vs. Microsoft Azure SQL Database vs. RocksDB vs. TerminusDB

System Properties Comparison Apache Druid vs. Microsoft Azure SQL Database vs. RocksDB vs. TerminusDB

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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

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
RDF 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	77.99
Rank	#16	Overall
	#11	Relational DBMS

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

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

druid.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

rocksdb.org

terminusdb.com

Technical documentation

druid.apache.org/docs/latest/design

docs.microsoft.com/en-us/azure/azure-sql

github.com/facebook/rocksdb/wiki

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation and contributors

Microsoft

Facebook, Inc.

DataChemist Ltd.

Initial release

2012

2010

2013

2018

Current release

29.0.1, April 2024

V12

8.11.4, April 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

BSD

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Prolog, Rust

Server operating systems

Linux
OS X
Unix

hosted

Linux

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

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

C++ API
Java API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes, with always 3 replicas available

yes

Journaling Streams

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

fine grained access rights according to SQL-standard

Role-based access control

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