DBMS > Adabas vs. Google BigQuery vs. Manticore Search vs. Spark SQL vs. Yaacomo

System Properties Comparison Adabas vs. Google BigQuery vs. Manticore Search vs. Spark SQL vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

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

Multi-storage database for search, including full-text search.

Spark SQL is a component on top of 'Spark Core' for structured data processing

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

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

cloud.google.com/bigquery

manticoresearch.com

spark.apache.org/sql

yaacomo.com

Technical documentation

cloud.google.com/bigquery/docs

manual.manticoresearch.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Software AG

Google

Manticore Software

Apache Software Foundation

Q2WEB GmbH

Initial release

1971

2010

2017

2014

2009

Current release

6.0, February 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Apache 2.0

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++

Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like query language

SQL-like DML and DDL statements

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

RESTful HTTP/JSON API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC

Supported programming languages

Natural

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

user defined functions

Triggers

yes

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

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

yes, utilizing Spark Core

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Synchronous replication based on Galera library

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

yes

isolated transactions for atomic changes and binary logging for safe writes

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 Manticore index.

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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