DBMS > Axibase vs. Faircom EDGE vs. Machbase Neo vs. MarkLogic vs. PouchDB

System Properties Comparison Axibase vs. Faircom EDGE vs. Machbase Neo vs. MarkLogic vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

TimeSeries DBMS for AIoT and BigData

Operational and transactional Enterprise NoSQL database

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

axibase.com/docs/atsd/finance

www.faircom.com/products/faircom-edge

machbase.com

www.marklogic.com

pouchdb.com

Technical documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

machbase.com/dbms

docs.marklogic.com

pouchdb.com/guides

Developer

Axibase Corporation

FairCom Corporation

Machbase

MarkLogic Corp.

Apache Software Foundation

Initial release

2013

1979

2013

2001

2012

Current release

15585

V3, October 2020

V8.0, August 2023

11.0, December 2022

7.1.1, June 2019

License

Commercial or Open Source

commercial

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

commercial

Restricted, free version available

commercial

free test version available

commercial

restricted free version is available

Open Source

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++

C++

JavaScript

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Windows

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

yes

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

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-like query language

yes

ANSI SQL queries

SQL-like query language

yes

SQL92

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via XQuery or JavaScript

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

volatile and lookup table

yes, with Range Indexes

yes

User concepts

Access control

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

simple password-based access control

Role-based access control at the document and subdocument levels

More information provided by the system vendor

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