DBMS > AgensGraph vs. ArcadeDB vs. Microsoft Azure Synapse Analytics vs. Tkrzw

System Properties Comparison AgensGraph vs. ArcadeDB vs. Microsoft Azure Synapse Analytics vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Graph DBMS
Relational DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Key-value store

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

Score	0.18
Rank	#315	Overall
	#28	Graph DBMS
	#141	Relational DBMS

Score	0.03
Rank	#360	Overall
	#51	Document stores
	#37	Graph DBMS
	#54	Key-value stores
	#37	Time Series DBMS

Score	16.84
Rank	#33	Overall
	#19	Relational DBMS

Score	0.00
Rank	#386	Overall
	#61	Key-value stores

Website

bitnine.net/agensgraph

arcadedb.com

azure.microsoft.com/services/synapse-analytics

dbmx.net/tkrzw

Technical documentation

bitnine.net/documentation

docs.arcadedb.com

docs.microsoft.com/azure/synapse-analytics

Developer

Bitnine Global Inc.

Arcade Data

Microsoft

Mikio Hirabayashi

Initial release

2016

2021

2016

2020

Current release

2.1, December 2018

September 2021

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 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

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

hosted

Linux
macOS

Data scheme

depending on used data model

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

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

yes

APIs and other access methods

Cypher Query Language
JDBC

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

ADO.NET
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

Java

C#
Java
PHP

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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