DBMS > Adabas vs. Google BigQuery vs. IBM Db2 Event Store vs. Kinetica vs. TypeDB

System Properties Comparison Adabas vs. Google BigQuery vs. IBM Db2 Event Store vs. Kinetica 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

Large scale data warehouse service with append-only tables

Distributed Event Store optimized for Internet of Things use cases

Fully vectorized database across both GPUs and CPUs

TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.

Primary database model

Multivalue DBMS

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Graph DBMS

The type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS

The data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS

The type-theoretic data model of TypeDB subsumes the relational database model.

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#8	Object oriented DBMS
	#106	Relational DBMS

Website

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

cloud.google.com/bigquery

www.ibm.com/products/db2-event-store

www.kinetica.com

typedb.com

Technical documentation

cloud.google.com/bigquery/docs

www.ibm.com/docs/en/db2-event-store

docs.kinetica.com

typedb.com/docs

Developer

Software AG

Google

IBM

Kinetica

Vaticle

Initial release

1971

2010

2017

2012

2016

Current release

2.0

7.1, August 2021

2.28.3, June 2024

License

Commercial or Open Source

commercial

free developer edition available

commercial

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 and C++

C, C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux

Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

through the embedded Spark runtime

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)

Supported programming languages

Natural

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C++
Java
JavaScript (Node.js)
Python

All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Active-active shard replication

Source-replica replication

Synchronous replication via raft

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

User concepts

Access control

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users and roles on table 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

Apache f or language drivers, and AGPL and Commercial for the database server. The...
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