DBMS > EXASOL vs. H2 vs. InfinityDB vs. RDFox vs. Snowflake

System Properties Comparison EXASOL vs. H2 vs. InfinityDB vs. RDFox vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

A Java embedded Key-Value Store which extends the Java Map interface

High performance knowledge graph and semantic reasoning engine

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.exasol.com

www.h2database.com

boilerbay.com

www.oxfordsemantic.tech

www.snowflake.com

Technical documentation

www.exasol.com/resources

www.h2database.com/html/main.html

boilerbay.com/infinitydb/manual

docs.oxfordsemantic.tech

docs.snowflake.net/manuals/index.html

Developer

Exasol

Thomas Mueller

Boiler Bay Inc.

Oxford Semantic Technologies

Snowflake Computing Inc.

Initial release

2000

2005

2002

2017

2014

Current release

2.2.220, July 2023

4.0

6.0, Septermber 2022

License

Commercial or Open Source

commercial

Open Source

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

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

Java

C++

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

hosted

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

RDF schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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.

yes

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API
SPARQL 1.1

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

Java

C
Java

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

Roles, resources, and access types

Users with fine-grained authorization concept, user roles and pluggable authentication

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