DBMS > GBase vs. Lovefield vs. ObjectBox vs. Sphinx vs. Trino

System Properties Comparison GBase vs. Lovefield vs. ObjectBox vs. Sphinx vs. Trino

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

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

www.gbase.cn

google.github.io/lovefield

github.com/objectbox
objectbox.io

sphinxsearch.com

trino.io

Technical documentation

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

docs.objectbox.io

sphinxsearch.com/docs

trino.io/broadcast
trino.io/docs/current

Developer

General Data Technology Co., Ltd.

Google

ObjectBox Limited

Sphinx Technologies Inc.

Trino Software Foundation

Initial release

2004

2014

2017

2001

2012

2020 rebranded from PrestoSQL

Current release

GBase 8a, GBase 8s, GBase 8c

2.1.12, February 2017

4.0 (May 2024)

3.5.1, February 2023

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

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, Java, Python

JavaScript

C and C++

C++

Java

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
macOS

for devlopment

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like 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

Secondary indexes

yes

full-text index on all search fields

depending on connected data-source

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

via JavaScript builder pattern

SQL-like query language (SphinxQL)

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

Proprietary native API

Proprietary protocol

JDBC
RESTful HTTP API
Trino CLI

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

yes, depending on connected data-source

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

depending on connected data-source

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

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

depending on connected data-source

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.

depending on connected data-source

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

SQL standard access control

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

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

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

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