DBMS > Graph Engine vs. Microsoft Azure Synapse Analytics vs. Stardog vs. XTDB

System Properties Comparison Graph Engine vs. Microsoft Azure Synapse Analytics vs. Stardog vs. XTDB

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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

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Graph DBMS
RDF store

Document store

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

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.graphengine.io

azure.microsoft.com/services/synapse-analytics

www.stardog.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.graphengine.io/docs/manual

docs.microsoft.com/azure/synapse-analytics

docs.stardog.com

www.xtdb.com/docs

Developer

Microsoft

Stardog-Union

Juxt Ltd.

Initial release

2010

2016

2010

2019

Current release

7.3.0, May 2020

1.19, September 2021

License

Commercial or Open Source

Open Source

MIT License

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

MIT License

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++

Java

Clojure

Server operating systems

.NET

hosted

Linux
macOS
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

HTTP REST
JDBC

Supported programming languages

C#
C++
F#
Visual Basic

C#
Java
PHP

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

yes

Transact SQL

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in HA-Cluster

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

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

yes

relationships in graphs

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

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

yes

Access rights for users and roles

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More resources

Recent citations in the news

Trinity
30 October 2010, microsoft.com

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019
27 February 2019, Data Science Central

provided by Google News

General Available: Azure Synapse Runtime for Apache Spark 3.4 is now GA
8 April 2024, azure.microsoft.com

Azure Synapse Runtime for Apache Spark 3.2 End of Support
22 March 2024, azure.microsoft.com

Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

Announcing General Availability of Graph Semantics in Kusto
27 May 2024, azure.microsoft.com

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT
18 October 2023, AWS Blog

provided by Google News

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