DBMS > Adabas vs. Google BigQuery vs. Lovefield vs. SiteWhere vs. Yaacomo

System Properties Comparison Adabas vs. Google BigQuery vs. Lovefield vs. SiteWhere 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

Embeddable relational database for web apps written in pure JavaScript

M2M integration platform for persisting/querying time series data

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

Primary database model

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	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

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

cloud.google.com/bigquery

google.github.io/lovefield

github.com/sitewhere/sitewhere

yaacomo.com

Technical documentation

cloud.google.com/bigquery/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

sitewhere1.sitewhere.io/index.html

Developer

Software AG

Google

SiteWhere

Q2WEB GmbH

Initial release

1971

2010

2014

2010

2009

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

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

JavaScript

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

predefined 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

SQL-like query language

via JavaScript builder pattern

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

HTTP REST

JDBC
ODBC

Supported programming languages

Natural

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

Triggers

Using read-only observers

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

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

selectable replication factor

based on HBase

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

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)

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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