DBMS > BaseX vs. Hypertable vs. Microsoft Azure Cosmos DB vs. Percona Server for MongoDB vs. SQream DB

System Properties Comparison BaseX vs. Hypertable vs. Microsoft Azure Cosmos DB vs. Percona Server for MongoDB vs. SQream DB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

An open source BigTable implementation based on distributed file systems such as Hadoop

Globally distributed, horizontally scalable, multi-model database service

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Native XML DBMS

Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

basex.org

azure.microsoft.com/services/cosmos-db

www.percona.com/mongodb/software/percona-server-for-mongodb

sqream.com

Technical documentation

docs.basex.org

learn.microsoft.com/azure/cosmos-db

docs.percona.com/percona-distribution-for-mongodb

docs.sqream.com

Developer

BaseX GmbH

Hypertable Inc.

Microsoft

Percona

SQream Technologies

Initial release

2007

2009

2014

2015

2017

Current release

10.7, August 2023

0.9.8.11, March 2016

3.4.10-2.10, November 2017

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

BSD license

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPL Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

JSON types

yes

yes, ANSI Standard SQL Types

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

restricted

only exact value or prefix value scans

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

C++ API
Thrift

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

proprietary protocol using JSON

.Net
JDBC
ODBC

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C++
Java
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions in Python

Triggers

yes

via events

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor on file system level

yes

Implicit feature of the cloud service

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Multi-item ACID transactions with snapshot isolation within a partition

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

via In-Memory Engine

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Access rights can be defined down to the item level

Access rights for users and roles

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