DBMS > EXASOL vs. IRONdb vs. SiteWhere vs. SwayDB vs. TerarkDB

System Properties Comparison EXASOL vs. IRONdb vs. SiteWhere vs. SwayDB vs. TerarkDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

M2M integration platform for persisting/querying time series data

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

www.exasol.com

www.circonus.com/solutions/time-series-database/

github.com/sitewhere/sitewhere

swaydb.simer.au

github.com/bytedance/terarkdb

Technical documentation

www.exasol.com/resources

docs.circonus.com/irondb/category/getting-started

sitewhere1.sitewhere.io/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Exasol

Circonus LLC.

SiteWhere

Simer Plaha

ByteDance, originally Terark

Initial release

2000

2017

2010

2018

2016

Current release

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

GNU Affero GPL V3.0

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

C and C++

Java

Scala

C++

Server operating systems

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HTTP API

HTTP REST

C++ API
Java API

Supported programming languages

Java
Lua
Python
R

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Java
Kotlin
Scala

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

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

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

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
20 March 2024, Business Wire

It's Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

Exasol Unveils New Suite of AI Tools to Turbocharge Enterprise Data Analytics
22 February 2024, AiThority

Exasol Reimagines In-Memory Analytics with Major Database Update
30 May 2023, Datanami

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding
22 February 2024, Datanami

Apica Acquires Circonus
21 February 2024, Destination CRM

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

A Chinese company is making the cloud 200x faster · TechNode
3 July 2017, TechNode

provided by Google News

Share this page