DBMS > Derby vs. Heroic vs. SiteWhere vs. TerarkDB

System Properties Comparison Derby vs. Heroic vs. SiteWhere vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

M2M integration platform for persisting/querying time series data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

db.apache.org/derby

github.com/spotify/heroic

github.com/sitewhere/sitewhere

github.com/bytedance/terarkdb

Technical documentation

db.apache.org/derby/manuals/index.html

spotify.github.io/heroic

sitewhere1.sitewhere.io/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Spotify

SiteWhere

ByteDance, originally Terark

Initial release

1997

2014

2010

2016

Current release

10.17.1.0, November 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

commercial

restricted open source 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

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

schema-free

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

via Elasticsearch

SQL

Support of SQL

yes

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP REST

C++ API
Java API

Supported programming languages

Java

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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