DBMS > GBase vs. Lovefield vs. ObjectBox vs. Sphinx vs. SWC-DB

System Properties Comparison GBase vs. Lovefield vs. ObjectBox vs. Sphinx vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

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

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Search engine

Wide column store

Secondary database models

Time Series DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

www.gbase.cn

google.github.io/lovefield

github.com/objectbox
objectbox.io

sphinxsearch.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.objectbox.io

sphinxsearch.com/docs

Developer

General Data Technology Co., Ltd.

Google

ObjectBox Limited

Sphinx Technologies Inc.

Alex Kashirin

Initial release

2004

2014

2017

2001

2020

Current release

GBase 8a, GBase 8s, GBase 8c

2.1.12, February 2017

4.0 (May 2024)

3.5.1, February 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

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

JavaScript

C and C++

C++

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like 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

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

via JavaScript builder pattern

SQL-like query language (SphinxQL)

SQL-like query language

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

Proprietary native API

Proprietary protocol

Proprietary protocol
Thrift

Supported programming languages

JavaScript

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Data sync between devices allowing occasional connected databases to work completely offline

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

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

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

yes

More information provided by the system vendor

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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