DBMS > Lovefield vs. OushuDB vs. XTDB

System Properties Comparison Lovefield vs. OushuDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

google.github.io/lovefield

www.oushu.com/product/oushuDB

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.oushu.com/documentation

www.xtdb.com/docs

Developer

Google

Oushu

Juxt Ltd.

Initial release

2014

2019

Current release

2.1.12, February 2017

4.0.1, August 2020

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

MIT License

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

JavaScript

Clojure

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like query language

via JavaScript builder pattern

Full-featured ANSI SQL support

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

JavaScript

C
C++

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Kerberos, SSL and role based access

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