DBMS > Apache Druid vs. CockroachDB vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

System Properties Comparison Apache Druid vs. CockroachDB vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

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.

Cloud-based data warehousing service

Cloud-based data warehousing service for structured and semi-structured data

a GPU-based, columnar RDBMS for big data analytics workloads

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	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

druid.apache.org

www.cockroachlabs.com

www.ibm.com/products/db2/warehouse

www.snowflake.com

sqream.com

Technical documentation

druid.apache.org/docs/latest/design

www.cockroachlabs.com/docs

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Apache Software Foundation and contributors

Cockroach Labs

IBM

Snowflake Computing Inc.

SQream Technologies

Initial release

2012

2015

2014

2017

Current release

29.0.1, April 2024

23.1.1, May 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0, commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
OS X
Unix

Linux
macOS
Windows

hosted

Linux

Data scheme

yes

schema-less columns are supported

dynamic schema

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL 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.

Import/export of XML data possible

yes

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

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

user defined functions

user defined functions in Python

Triggers

yes

similar concept for controling cloud resources

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

Sharding

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication using RAFT

yes

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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