DBMS > DataFS vs. GBase vs. Linter vs. QuestDB vs. Sphinx

System Properties Comparison DataFS vs. GBase vs. Linter vs. QuestDB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

RDBMS for high security requirements

A high performance open source SQL database for time series data

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Graph DBMS

Spatial DBMS

Relational DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

Technical documentation

dev.mobiland.com/Overview.xsp

questdb.io/docs

sphinxsearch.com/docs

Developer

Mobiland AG

General Data Technology Co., Ltd.

relex.ru

QuestDB Technology Inc

Sphinx Technologies Inc.

Initial release

2018

2004

1990

2014

2001

Current release

1.1.263, October 2022

GBase 8a, GBase 8s, GBase 8c

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2, commercial licence available

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, Java, Python

C and C++

Java (Zero-GC), C++, Rust

C++

Server operating systems

Windows

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free via InfluxDB Line Protocol

yes

Typing

predefined data types such as float or date

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

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

Standard with numerous extensions

yes

SQL with time-series extensions

SQL-like query language (SphinxQL)

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Proprietary protocol

Supported programming languages

.Net
C
C#
C++
VB.Net

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

horizontal partitioning (by range, list and hash) and vertical partitioning

none

horizontal partitioning (by timestamps)

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Source-replica replication with eventual consistency

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

through memory mapped files

User concepts

Access control

Windows-Profile

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

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10 September 2024

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4 September 2024

Building a new vector based storage model
22 August 2024

Calibrating VWAP executions with QuestDB and Grafana
16 August 2024

Write Time: a call for community writers
13 August 2024

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More resources

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