DBMS > Adabas vs. AnzoGraph DB vs. Google Cloud Firestore vs. Microsoft Azure Synapse Analytics vs. Snowflake

System Properties Comparison Adabas vs. AnzoGraph DB vs. Google Cloud Firestore vs. Microsoft Azure Synapse Analytics vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

Primary database model

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

cambridgesemantics.com/anzograph

firebase.google.com/products/firestore

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

firebase.google.com/docs/firestore

docs.microsoft.com/azure/synapse-analytics

docs.snowflake.net/manuals/index.html

Developer

Software AG

Cambridge Semantics

Google

Microsoft

Snowflake Computing Inc.

Initial release

1971

2018

2017

2016

2014

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

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

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

Data scheme

yes

Schema-free and OWL/RDFS-schema support

schema-free

yes

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

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

with add-on product Adabas SQL Gateway

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Natural

C++
Java
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C#
Java
PHP

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

user defined functions and aggregates

yes, Firebase Rules & Cloud Functions

Transact SQL

user defined functions

Triggers

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Automatic sharding

Sharding

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication in MPP-Cluster

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

yes

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

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

yes

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

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