DBMS > Graph Engine vs. Microsoft Azure Table Storage vs. WakandaDB vs. Warp 10

System Properties Comparison Graph Engine vs. Microsoft Azure Table Storage vs. WakandaDB vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A Wide Column Store for rapid development using massive semi-structured datasets

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Graph DBMS
Key-value store

Wide column store

Object oriented DBMS

Time Series DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.graphengine.io

azure.microsoft.com/en-us/services/storage/tables

wakanda.github.io

www.warp10.io

Technical documentation

www.graphengine.io/docs/manual

wakanda.github.io/doc

www.warp10.io/content/02_Getting_started

Developer

Microsoft

Wakanda SAS

SenX

Initial release

2010

2012

2015

Current release

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

AGPLv3, extended commercial license available

Open Source

Apache License 2.0

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

.NET and C

C++, JavaScript

Java

Server operating systems

.NET

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
F#
Visual Basic

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

JavaScript

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

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