DBMS > eXtremeDB vs. Heroic vs. Quasardb vs. SWC-DB vs. Warp 10

System Properties Comparison eXtremeDB vs. Heroic vs. Quasardb vs. SWC-DB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Distributed, high-performance timeseries database

A high performance, scalable Wide Column DBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Wide column store

Time Series DBMS

Secondary database models

Time Series DBMS

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.mcobject.com

github.com/spotify/heroic

quasar.ai

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

www.warp10.io

Technical documentation

www.mcobject.com/docs/extremedb.htm

spotify.github.io/heroic

doc.quasar.ai/master

www.warp10.io/content/02_Getting_started

Developer

McObject

Spotify

quasardb

Alex Kashirin

SenX

Initial release

2001

2014

2009

2020

2015

Current release

8.2, 2021

3.14.1, January 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPL V3

Open Source

Apache License 2.0

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

C and C++

Java

C++

Java

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

BSD
Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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.

support of XML interfaces available

Secondary indexes

yes

via Elasticsearch

yes

with tags

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

HTTP API

Proprietary protocol
Thrift

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

consistent hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

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

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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