DBMS > Apache Druid vs. openGauss vs. RocksDB vs. Snowflake

System Properties Comparison Apache Druid vs. openGauss vs. RocksDB vs. Snowflake

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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

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial 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	1.08
Rank	#183	Overall
	#84	Relational DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

druid.apache.org

gitee.com/opengauss
opengauss.org

rocksdb.org

www.snowflake.com

Technical documentation

druid.apache.org/docs/latest/design

docs.opengauss.org/en
gitee.com/opengauss/docs

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Huawei and openGauss community

Facebook, Inc.

Snowflake Computing Inc.

Initial release

2012

2019

2013

2014

Current release

29.0.1, April 2024

3.0, March 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD

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, C++, Java

C++

Server operating systems

Linux
OS X
Unix

Linux

hosted

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

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

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

ANSI SQL 2011

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

C++ API
Java API

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

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 range, list and hash)

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

yes

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 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

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

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

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