DBMS > Cachelot.io vs. IBM Db2 Event Store vs. IRONdb vs. SwayDB

System Properties Comparison Cachelot.io vs. IBM Db2 Event Store vs. IRONdb vs. SwayDB

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Editorial information provided by DB-Engines

Name

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

Description

In-memory caching system

Distributed Event Store optimized for Internet of Things use cases

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

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

Primary database model

Key-value store

Event Store
Time Series DBMS

Time Series DBMS

Key-value store

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

cachelot.io

www.ibm.com/products/db2-event-store

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

swaydb.simer.au

Technical documentation

www.ibm.com/docs/en/db2-event-store

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

Developer

IBM

Circonus LLC.

Simer Plaha

Initial release

2015

2017

2018

Current release

2.0

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

free developer edition available

commercial

Open Source

GNU Affero GPL V3.0

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++

C and C++

Scala

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL

Support of SQL

yes

through the embedded Spark runtime

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

APIs and other access methods

Memcached protocol

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard replication

configurable replication factor, datacenter aware

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

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