DBMS > Adabas vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. TypeDB

System Properties Comparison Adabas vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. TypeDB

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

Globally distributed, horizontally scalable, multi-model database service

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

Open source search engine for searching in data from different sources, e.g. relational databases

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Multivalue DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Search engine

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

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

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

sphinxsearch.com

typedb.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

sphinxsearch.com/docs

typedb.com/docs

Developer

Software AG

Microsoft

Sphinx Technologies Inc.

Vaticle

Initial release

1971

2014

2016

2001

2016

Current release

3.5.1, February 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial licence available

Open Source

GPL Version 3, commercial licenses available

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++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

Proprietary protocol

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

Natural

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
PHP

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

in Natural

JavaScript

Transact SQL

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Implicit feature of the cloud service

yes

none

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

substituted by the relationship feature

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

Access rights can be defined down to the item level

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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