DBMS > Axibase vs. Elasticsearch vs. Faircom DB vs. FatDB

System Properties Comparison Axibase vs. Elasticsearch vs. Faircom DB vs. FatDB

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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.

Description

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Primary database model

Time Series DBMS

Search engine

Key-value store
Relational DBMS

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Website

axibase.com/docs/atsd/finance

www.elastic.co/elasticsearch

www.faircom.com/products/faircom-db

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

Developer

Axibase Corporation

Elastic

FairCom Corporation

FatCloud

Initial release

2013

2010

1979

2012

Current release

15585

8.6, January 2023

V12, November 2020

License

Commercial or Open Source

commercial

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

Open Source

Elastic License

commercial

Restricted, free version 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

ANSI C, C++

Server operating systems

Linux

All OS with a Java VM

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes

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

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes, ANSI SQL with proprietary extensions

Via inetgration in SQL Server

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via applications

Triggers

yes

by using the 'percolation' feature

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Can implement custom security layer via applications

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More resources

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