DBMS > HugeGraph vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Percona Server for MongoDB vs. WakandaDB

System Properties Comparison HugeGraph vs. Microsoft Azure Synapse Analytics vs. NSDb vs. Percona Server for MongoDB vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

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

Primary database model

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/services/synapse-analytics

nsdb.io

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

wakanda.github.io

Technical documentation

hugegraph.apache.org/docs

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

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

wakanda.github.io/doc

Developer

Baidu

Microsoft

Percona

Wakanda SAS

Initial release

2018

2016

2017

2015

2012

Current release

0.9

3.4.10-2.10, November 2017

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

GPL Version 2

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++

Java, Scala

C++

C++, JavaScript

Server operating systems

Linux
macOS
Unix

hosted

Linux
macOS

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, 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

also supports composite index and range index

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

proprietary protocol using JSON

RESTful HTTP API

Supported programming languages

Groovy
Java
Python

C#
Java
PHP

Java
Scala

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

JavaScript

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Transact SQL

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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, roles and permissions

yes

Access rights for users and roles

yes

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