DBMS > Kyligence Enterprise vs. Microsoft Azure Cosmos DB vs. STSdb vs. WakandaDB

System Properties Comparison Kyligence Enterprise vs. Microsoft Azure Cosmos DB vs. STSdb vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, built on top of Apache Kylin

Globally distributed, horizontally scalable, multi-model database service

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

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

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

kyligence.io/kyligence-enterprise

azure.microsoft.com/services/cosmos-db

github.com/STSSoft/STSdb4

wakanda.github.io

Technical documentation

learn.microsoft.com/azure/cosmos-db

wakanda.github.io/doc

Developer

Kyligence, Inc.

Microsoft

STS Soft SC

Wakanda SAS

Initial release

2016

2014

2011

2012

Current release

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

Open Source

AGPLv3, extended commercial license available

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

C++, JavaScript

Server operating systems

Linux

hosted

Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

primitive types and user defined types (classes)

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 properties auto-indexed by default

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

.NET Client API

RESTful HTTP API

Supported programming languages

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

C#
Java

JavaScript

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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.

User concepts

Access control

Access rights can be defined down to the item level

yes

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