DBMS > FatDB vs. Postgres-XL vs. Spark SQL vs. SQream DB

System Properties Comparison FatDB vs. Postgres-XL vs. Spark SQL vs. SQream DB

Please select another system to include it in the comparison.

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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Spark SQL is a component on top of 'Spark Core' for structured data processing

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

www.postgres-xl.org

spark.apache.org/sql

sqream.com

Technical documentation

www.postgres-xl.org/documentation

spark.apache.org/docs/latest/sql-programming-guide.html

docs.sqream.com

Developer

FatCloud

Apache Software Foundation

SQream Technologies

Initial release

2012

2014

since 2012, originally named StormDB

2014

2017

Current release

10 R1, October 2018

3.5.0 ( 2.13), September 2023

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Scala

C++, CUDA, Haskell, Java, Scala

Server operating systems

Windows

Linux
macOS

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

distributed, parallel query execution

SQL-like DML and DDL statements

yes

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
Python
R
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

user defined functions

user defined functions in Python

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes, utilizing Spark Core

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

MVCC

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.

User concepts

Access control

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

I SQream, you SQream, we all SQream for … data analytics?
5 October 2023, fierce-network.com

SQream Announces Strategic Integration for Powerful Big Data Analytics with Dataiku
9 February 2024, insideBIGDATA

GPU data warehouse startup SQream lands $39.4M funding round
24 June 2020, SiliconANGLE News

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

SQream Announces Free Licenses to Organizations Using Data Analytics to Fight the Coronavirus
9 April 2020, Embedded Computing Design

provided by Google News

Share this page