DBMS > Amazon DocumentDB vs. EDB Postgres vs. Microsoft Azure Synapse Analytics vs. Snowflake vs. Teradata

System Properties Comparison Amazon DocumentDB vs. EDB Postgres vs. Microsoft Azure Synapse Analytics vs. Snowflake vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

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 hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

aws.amazon.com/documentdb

www.enterprisedb.com

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

www.teradata.com

Technical documentation

aws.amazon.com/documentdb/resources

www.enterprisedb.com/docs

docs.microsoft.com/azure/synapse-analytics

docs.snowflake.net/manuals/index.html

docs.teradata.com

Developer

EnterpriseDB

Microsoft

Snowflake Computing Inc.

Teradata

Initial release

2019

2005

2016

2014

1984

Current release

14, December 2021

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

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

hosted

Linux
Windows

hosted

hosted
Linux

Data scheme

schema-free

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL 2016 + extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

C#
Java
PHP

JavaScript (Node.js)
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Transact SQL

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

by hash, list or range

Sharding, horizontal partitioning

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

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

fine grained access rights according to SQL-standard

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