DBMS > ArcadeDB vs. Blueflood vs. HugeGraph vs. Microsoft SQL Server vs. Percona Server for MySQL

System Properties Comparison ArcadeDB vs. Blueflood vs. HugeGraph vs. Microsoft SQL Server vs. Percona Server for MySQL

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Scalable TimeSeries DBMS based on Cassandra

A fast-speed and highly-scalable Graph DBMS

Microsofts flagship relational DBMS

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Time Series DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Website

arcadedb.com

blueflood.io

github.com/hugegraph
hugegraph.apache.org

www.microsoft.com/en-us/sql-server

www.percona.com/software/mysql-database/percona-server

Technical documentation

docs.arcadedb.com

github.com/rax-maas/blueflood/wiki

hugegraph.apache.org/docs

learn.microsoft.com/en-US/sql/sql-server

www.percona.com/downloads/Percona-Server-LATEST

Developer

Arcade Data

Rackspace

Baidu

Microsoft

Percona

Initial release

2021

2013

2018

1989

2008

Current release

September 2021

0.9

SQL Server 2022, November 2022

8.0.36-28, 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C and C++

Server operating systems

All OS with a Java VM

Linux
OS X

Linux
macOS
Unix

Linux
Windows

Linux

Data scheme

schema-free

predefined scheme

yes

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC

Supported programming languages

Java

Groovy
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

yes

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

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication
XtraDB Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

edges in graph

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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