DBMS > Lovefield vs. Quasardb vs. Vitess vs. XTDB

System Properties Comparison Lovefield vs. Quasardb vs. Vitess vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Distributed, high-performance timeseries database

Scalable, distributed, cloud-native DBMS, extending MySQL

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

google.github.io/lovefield

quasar.ai

vitess.io

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

Technical documentation

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

doc.quasar.ai/master

vitess.io/docs

www.xtdb.com/docs

Developer

Google

quasardb

The Linux Foundation, PlanetScale

Juxt Ltd.

Initial release

2014

2009

2013

2019

Current release

2.1.12, February 2017

3.14.1, January 2024

15.0.2, December 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 2.0, commercial licenses available

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

C++

Clojure

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

BSD
Linux
OS X
Windows

Docker
Linux
macOS

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

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP REST
JDBC

Supported programming languages

JavaScript

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

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

yes

by using LevelDB

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

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

no user groups or roles

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