DBMS > RocksDB vs. SiteWhere vs. StarRocks

System Properties Comparison RocksDB vs. SiteWhere vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

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

M2M integration platform for persisting/querying time series data

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

Forked from Apache Doris

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

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

Score	2.89
Rank	#97	Overall
	#16	Key-value stores

Score	0.06
Rank	#346	Overall
	#32	Time Series DBMS

Score	0.75
Rank	#218	Overall
	#101	Relational DBMS

Website

rocksdb.org

github.com/sitewhere/sitewhere

www.starrocks.io

Technical documentation

github.com/facebook/rocksdb/wiki

sitewhere1.sitewhere.io/index.html

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

Developer

Facebook, Inc.

SiteWhere

The Linux Foundation

since Feb 2023

Initial release

2013

2010

2020

Current release

9.4.0, June 2024

3.3, June 2024

License

Commercial or Open Source

Open Source

BSD

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Java

C++, Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

Data scheme

schema-free

predefined scheme

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

yes

APIs and other access methods

C++ API
Java API

HTTP REST

JDBC
MySQL protocol

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Java

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on HBase

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

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

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

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

Users with fine-grained authorization concept

Role based access control and fine grained access rights

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