DBMS > Adabas vs. Amazon CloudSearch vs. Blazegraph vs. RocksDB vs. TimescaleDB

System Properties Comparison Adabas vs. Amazon CloudSearch vs. Blazegraph vs. RocksDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

A hosted search engine service by Amazon with the data stored in Amazons cloud

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

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	1.81
Rank	#137	Overall
	#12	Search engines

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

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

aws.amazon.com/cloudsearch

blazegraph.com

rocksdb.org

www.timescale.com

Technical documentation

docs.aws.amazon.com/cloudsearch

wiki.blazegraph.com

github.com/facebook/rocksdb/wiki

docs.timescale.com

Developer

Software AG

Amazon

Blazegraph

Facebook, Inc.

Timescale

Initial release

1971

2012

2006

2013

2017

Current release

2.1.5, March 2019

9.2.1, May 2024

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

BSD

Open Source

Apache 2.0

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

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SPARQL is used as query language

yes

full PostgreSQL SQL syntax

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

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

C++ API
Java API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Natural

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

in Natural

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

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

yes

automatic partitioning across Amazon Search Instance as required

Sharding

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

managed transparently by AWS

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

yes

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)

authentication via encrypted signatures

Security and Authentication via Web Application Container (Tomcat, Jetty)

fine grained access rights according to SQL-standard

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