DBMS > Datomic vs. Microsoft Azure Synapse Analytics vs. SAP SQL Anywhere vs. ToroDB

System Properties Comparison Datomic vs. Microsoft Azure Synapse Analytics vs. SAP SQL Anywhere vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Document store

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

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Website

www.datomic.com

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/technology-platform/sql-anywhere.html

github.com/torodb/server

Technical documentation

docs.datomic.com

docs.microsoft.com/azure/synapse-analytics

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Cognitect

Microsoft

SAP

formerly Sybase

8Kdata

Initial release

2012

2016

1992

2016

Current release

1.0.6735, June 2023

17, July 2015

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

AGPL-V3

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, Clojure

C++

Java

Server operating systems

All OS with a Java VM

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Clojure
Java

C#
Java
PHP

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

Transact SQL

yes, in C/C++, Java, .Net or Perl

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Source-replica replication

Database mirroring

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

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