DBMS > Apache Druid vs. Kyligence Enterprise vs. Snowflake vs. STSdb vs. SWC-DB

System Properties Comparison Apache Druid vs. Kyligence Enterprise vs. Snowflake vs. STSdb vs. SWC-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

A distributed analytics engine for big data, built on top of Apache Kylin

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Wide column store

Secondary database models

Time Series 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	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

druid.apache.org

kyligence.io/kyligence-enterprise

www.snowflake.com

github.com/STSSoft/STSdb4

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

druid.apache.org/docs/latest/design

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Kyligence, Inc.

Snowflake Computing Inc.

STS Soft SC

Alex Kashirin

Initial release

2012

2016

2014

2011

2020

Current release

29.0.1, April 2024

4.0.8, September 2015

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

GPLv2, commercial license available

Open Source

GPL V3

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++

Server operating systems

Linux
OS X
Unix

Linux

hosted

Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

ANSI SQL for queries (using Apache Calcite)

yes

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

.NET Client API

Proprietary protocol
Thrift

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript (Node.js)
Python

C#
Java

C++

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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.

User concepts

Access control

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

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

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