DBMS > Adabas vs. JanusGraph vs. Lovefield vs. Vertica

System Properties Comparison Adabas vs. JanusGraph vs. Lovefield vs. Vertica

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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 Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Embeddable relational database for web apps written in pure JavaScript

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Multivalue DBMS

Graph DBMS

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	11.40
Rank	#43	Overall
	#27	Relational DBMS

Website

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

janusgraph.org

google.github.io/lovefield

www.vertica.com

Technical documentation

docs.janusgraph.org

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

vertica.com/documentation

Developer

Software AG

Linux Foundation; originally developed as Titan by Aurelius

Google

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1971

2017

2014

2005

Current release

0.6.3, February 2023

2.1.12, February 2017

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X
Unix
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

via JavaScript builder pattern

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Natural

Clojure
Java
Python

JavaScript

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

in Natural

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Using read-only observers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User concepts

Access control

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

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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