DBMS > Lovefield vs. ObjectBox vs. Pinecone vs. Sphinx vs. VoltDB

System Properties Comparison Lovefield vs. ObjectBox vs. Pinecone vs. Sphinx vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Extremely fast embedded database for small devices, IoT and Mobile

A managed, cloud-native vector database

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	3.23
Rank	#92	Overall
	#2	Vector DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

google.github.io/lovefield

Technical documentation

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

docs.objectbox.io

docs.pinecone.io/docs/overview

sphinxsearch.com/docs

docs.voltdb.com

Developer

Google

ObjectBox Limited

Pinecone Systems, Inc

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2014

2017

2019

2001

2010

Current release

2.1.12, February 2017

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

commercial

Open Source

GPL version 2, commercial licence available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

JavaScript

C and C++

C++

Java, C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Android
iOS
Linux
macOS
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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.

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

Proprietary native API

RESTful HTTP API

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

JavaScript

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

online/offline synchronization between client and server

none

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

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

Snapshots and command logging

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

Users and roles with access to stored procedures

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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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

Vector databases
2 June 2023, Matthias Gelbmann

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The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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