DBMS > FatDB vs. Postgres-XL vs. SQream DB vs. Tigris

System Properties Comparison FatDB vs. Postgres-XL vs. SQream DB vs. Tigris

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

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Key-value store
Search engine
Time Series 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	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

www.postgres-xl.org

sqream.com

www.tigrisdata.com

Technical documentation

www.postgres-xl.org/documentation

docs.sqream.com

www.tigrisdata.com/docs

Developer

FatCloud

SQream Technologies

Tigris Data, Inc.

Initial release

2012

2014

since 2012, originally named StormDB

2017

2022

Current release

10 R1, October 2018

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

commercial

Open Source

Apache Version 2.0

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

C++, CUDA, Haskell, Java, Scala

Server operating systems

Windows

Linux
macOS

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

distributed, parallel query execution

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

.Net
JDBC
ODBC

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)

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

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

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

yes, using FoundationDB

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

Access rights for users and roles

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

I SQream, you SQream, we all SQream for … data analytics?
5 October 2023, Fierce Network

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

Accelerated Databases In The Fast Lane
25 June 2020, The Next Platform

SQream Launches IoT Edge Partner Innovation Lab to Bring Data Management, Analytics, AI at the Edge
10 May 2019, TechDecisions

provided by Google News

Tigris Data Unveils Beta Launch of New Vector Search Tool
19 May 2023, Datanami

Tigris Data Launches All-in-One Developer Data Platform
27 September 2022, Datanami

FerretDB Provides Alternative to MongoDB
19 May 2023, Datanami

Latest Asigra platform targets SaaS backup for MSPs
6 March 2023, TechTarget

provided by Google News

Share this page