DBMS > EXASOL vs. eXtremeDB vs. InfinityDB vs. Percona Server for MySQL vs. Snowflake

System Properties Comparison EXASOL vs. eXtremeDB vs. InfinityDB vs. Percona Server for MySQL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

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

Score	2.10
Rank	#119	Overall
	#57	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.exasol.com

www.mcobject.com

boilerbay.com

www.percona.com/software/mysql-database/percona-server

www.snowflake.com

Technical documentation

www.exasol.com/resources

www.mcobject.com/docs/extremedb.htm

boilerbay.com/infinitydb/manual

www.percona.com/downloads/Percona-Server-LATEST

docs.snowflake.net/manuals/index.html

Developer

Exasol

McObject

Boiler Bay Inc.

Percona

Snowflake Computing Inc.

Initial release

2000

2001

2002

2008

2014

Current release

8.2, 2021

4.0

8.0.36-28, 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2

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

C and C++

Java

C and C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux

hosted

Data scheme

yes

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

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.

support of XML interfaces available

yes

Secondary indexes

yes

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

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

.Net
C
C#
C++
Java
Lua
Python
Scala

Java

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

by defining events

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

none

Multi-source replication
Source-replica replication
XtraDB Cluster

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

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Users with fine-grained authorization concept

no user groups or roles

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

More information provided by the system vendor

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Competitive advantages

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Key customers

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Market metrics

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Licensing and pricing models

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