DBMS > Axibase vs. Couchbase vs. FatDB vs. IRONdb

System Properties Comparison Axibase vs. Couchbase vs. FatDB vs. IRONdb

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Primary database model

Time Series DBMS

Document store

Document store
Key-value store

Time Series DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Website

axibase.com/docs/atsd/finance

www.couchbase.com

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

Technical documentation

docs.couchbase.com

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

Developer

Axibase Corporation

Couchbase, Inc.

FatCloud

Circonus LLC.

Initial release

2013

2011

2012

2017

Current release

15585

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

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, C++, Go and Erlang

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

yes

SQL

Support of SQL

SQL-like query language

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

Via inetgration in SQL Server

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

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

via applications

yes, in Lua

Triggers

yes

via the TAP protocol

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

Sharding

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

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

Ephemeral buckets

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Can implement custom security layer via applications

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