DBMS > EsgynDB vs. FatDB vs. SvectorDB

System Properties Comparison EsgynDB vs. FatDB vs. SvectorDB

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Serverless cloud-native vector database

Primary database model

Relational DBMS

Document store
Key-value store

Vector DBMS

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

Score	0.19
Rank	#317	Overall
	#140	Relational DBMS

Score	0.02
Rank	#374	Overall
	#21	Vector DBMS

Website

www.esgyn.cn

svectordb.com

Technical documentation

www.svectordb.com/docs

Developer

Esgyn

FatCloud

SvectorDB

Initial release

2015

2012

2023

License

Commercial or Open Source

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++, Java

Server operating systems

Linux

Windows

server-less

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, double, vector

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Via inetgration in SQL Server

APIs and other access methods

ADO.NET
JDBC
ODBC

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

OpenAPI 3.0, RESTful HTTP API, Python SDK, JavaScript / TypeScript SDK

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

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.

Share this page