DBMS > FatDB vs. H2 vs. Realm vs. VelocityDB vs. Vertica

System Properties Comparison FatDB vs. H2 vs. Realm vs. VelocityDB vs. Vertica

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

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

Document store
Key-value store

Relational DBMS

Document store

Graph DBMS
Object oriented DBMS

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

Technical documentation

www.h2database.com/html/main.html

realm.io/docs

velocitydb.com/UserGuide

vertica.com/documentation

Developer

FatCloud

Thomas Mueller

Realm, acquired by MongoDB in May 2019

VelocityDB Inc

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2005

2014

2011

2005

Current release

2.2.220, July 2023

7.x

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Windows

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

Any that supports .NET

Linux

Data scheme

schema-free

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

Via inetgration in SQL Server

yes

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

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC

.Net

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

character-based, interactive, front-end utility

Supported programming languages

Java

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net

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

Server-side scripts

Stored procedures

yes

via applications

Java Stored Procedures and User-Defined Functions

runs within the applications so server-side scripts are unnecessary

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

via applications

yes

Change Listeners

Callbacks are triggered when data changes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

In-Memory realm

yes

User concepts

Access control

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

yes

Based on Windows Authentication

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...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

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...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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