DBMS > Dolt vs. Microsoft Azure Synapse Analytics vs. Snowflake vs. TigerGraph

System Properties Comparison Dolt vs. Microsoft Azure Synapse Analytics vs. Snowflake vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

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

Cloud-based data warehousing service for structured and semi-structured data

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store

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

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

github.com/dolthub/dolt
www.dolthub.com

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

www.tigergraph.com

Technical documentation

docs.dolthub.com

docs.microsoft.com/azure/synapse-analytics

docs.snowflake.net/manuals/index.html

docs.tigergraph.com

Developer

DoltHub Inc

Microsoft

Snowflake Computing Inc.

Initial release

2018

2016

2014

2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

C++

Server operating systems

Linux
macOS
Windows

hosted

Linux

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

yes

SQL-like query language (GSQL)

APIs and other access methods

CLI Client
HTTP REST

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java
PHP

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes

currently in alpha release

Transact SQL

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

In-memory capabilities

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

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

Role-based access control

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