DBMS > Apache Druid vs. Sadas Engine vs. StarRocks vs. TimesTen

System Properties Comparison Apache Druid vs. Sadas Engine vs. StarRocks vs. TimesTen

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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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

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	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

druid.apache.org

www.sadasengine.com

www.starrocks.io

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

druid.apache.org/docs/latest/design

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation and contributors

SADAS s.r.l.

The Linux Foundation

since Feb 2023

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2006

2020

1998

Current release

29.0.1, April 2024

8.0

2.5.3, March 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free trial version available

Open Source

Apache Version 2.0

commercial

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

C++

C++, Java

Server operating systems

Linux
OS X
Unix

AIX
Linux
Windows

Linux

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

Data scheme

yes

schema-less columns are supported

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.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

JDBC
MySQL protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

horizontal partitioning (by range and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

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 according to SQL-standard

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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