DBMS > Apache Pinot vs. EXASOL vs. Netezza vs. Snowflake vs. STSdb

System Properties Comparison Apache Pinot vs. EXASOL vs. Netezza vs. Snowflake vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Data warehouse and analytics appliance part of IBM PureSystems

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

pinot.apache.org

www.exasol.com

www.ibm.com/products/netezza

www.snowflake.com

github.com/STSSoft/STSdb4

Technical documentation

docs.pinot.apache.org

www.exasol.com/resources

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Exasol

IBM

Snowflake Computing Inc.

STS Soft SC

Initial release

2015

2000

2014

2011

Current release

1.0.0, September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license available

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

Server operating systems

All OS with a Java JDK11 or higher

Linux

included in appliance

hosted

Windows

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

.NET Client API

Supported programming languages

Go
Java
Python

Java
Lua
Python
R

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

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

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