DBMS > Adabas vs. Dolt vs. Google BigQuery vs. Ignite vs. Riak TS

System Properties Comparison Adabas vs. Dolt vs. Google BigQuery vs. Ignite vs. Riak TS

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

A MySQL compatible DBMS with Git-like versioning of data and schema

Large scale data warehouse service with append-only tables

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

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

github.com/dolthub/dolt
www.dolthub.com

cloud.google.com/bigquery

ignite.apache.org

Technical documentation

docs.dolthub.com

cloud.google.com/bigquery/docs

apacheignite.readme.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Software AG

DoltHub Inc

Google

Apache Software Foundation

Open Source, formerly Basho Technologies

Initial release

1971

2018

2010

2015

Current release

Apache Ignite 2.6

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

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, .Net

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
macOS
Windows

hosted

Linux
OS X
Solaris
Windows

Linux
OS X

Data scheme

yes

schema-free

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

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

ANSI-99 for query and DML statements, subset of DDL

yes, limited

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

CLI Client
HTTP REST

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API
Native Erlang Interface

Supported programming languages

Natural

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

in Natural

yes

currently in alpha release

user defined functions

in JavaScript

yes (compute grid and cache interceptors can be used instead)

Erlang

Triggers

yes

yes (cache interceptors and events)

yes

pre-commit hooks and post-commit hooks

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

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes (replicated cache)

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

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)

Only one user is configurable, and must be specified in the config file at startup

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

Google Cloud Identity & Access Management (IAM)

Security Hooks for custom implementations

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