DBMS > Axibase vs. Databend vs. IBM Cloudant vs. RDF4J

System Properties Comparison Axibase vs. Databend vs. IBM Cloudant vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Database as a Service offering based on Apache CouchDB

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

axibase.com/docs/atsd/finance

github.com/datafuselabs/databend
www.databend.com

www.ibm.com/products/cloudant

rdf4j.org

Technical documentation

docs.databend.com

cloud.ibm.com/docs/Cloudant

rdf4j.org/documentation

Developer

Axibase Corporation

Databend Labs

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2013

2021

2010

2004

Current release

15585

1.0.59, April 2023

License

Commercial or Open Source

commercial

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

Open Source

Apache Version 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Rust

Erlang

Java

Server operating systems

Linux

hosted
Linux
macOS

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

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

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

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

atomic operations within a document possible

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

User concepts

Access control

Users with fine-grained authorization concept, user roles

Access rights for users can be defined per database

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