DBMS > Apache Druid vs. CockroachDB vs. Sadas Engine

System Properties Comparison Apache Druid vs. CockroachDB vs. Sadas Engine

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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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	6.10
Rank	#58	Overall
	#33	Relational DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

druid.apache.org

www.cockroachlabs.com

www.sadasengine.com

Technical documentation

druid.apache.org/docs/latest/design

www.cockroachlabs.com/docs

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

Developer

Apache Software Foundation and contributors

Cockroach Labs

SADAS s.r.l.

Initial release

2012

2015

2006

Current release

29.0.1, April 2024

23.1.1, May 2023

8.0

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0, commercial license available

commercial

free trial version available

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++

Server operating systems

Linux
OS X
Unix

Linux
macOS
Windows

AIX
Linux
Windows

Data scheme

yes

schema-less columns are supported

dynamic schema

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, wire compatible with PostgreSQL

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

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

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication using RAFT

none

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.

yes

managed by 'Learn by Usage'

User concepts

Access control

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

Role-based access control

Access rights for users, groups and roles according to SQL-standard

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