DBMS > Adabas vs. Alibaba Cloud Table Store vs. CrateDB vs. Google BigQuery vs. Riak TS

System Properties Comparison Adabas vs. Alibaba Cloud Table Store vs. CrateDB vs. Google BigQuery 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 fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Distributed Database based on Lucene

Large scale data warehouse service with append-only tables

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

Primary database model

Multivalue DBMS

Wide column store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

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

www.alibabacloud.com/product/table-store

cratedb.com

cloud.google.com/bigquery

Technical documentation

www.alibabacloud.com/help/en/tablestore

cratedb.com/docs

cloud.google.com/bigquery/docs

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

Developer

Software AG

Alibaba

Crate

Google

Open Source, formerly Basho Technologies

Initial release

1971

2016

2013

2010

2015

Current release

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

commercial

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

Java

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux
OS X

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

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

HTTP API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

Natural

Java
Python

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

user defined functions (Javascript)

user defined functions

in JavaScript

Erlang

Triggers

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

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Implicit feature of the cloud service

Configurable replication on table/partition-level

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

ACID

Atomic single-row operations

unique row identifiers can be used for implementing an optimistic concurrency control strategy

Since BigQuery is designed for querying data

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.

User concepts

Access control

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

Access rights based on subaccounts and tokens

rights management via user accounts

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

Google Cloud Identity & Access Management (IAM)

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