DBMS > Lovefield vs. Microsoft Azure SQL Database vs. Qdrant vs. XTDB

System Properties Comparison Lovefield vs. Microsoft Azure SQL Database vs. Qdrant vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Database as a Service offering with high compatibility to Microsoft SQL Server

A high-performance vector database with neural network or semantic-based matching

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

Primary database model

Relational DBMS

Vector DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

google.github.io/lovefield

azure.microsoft.com/en-us/products/azure-sql/database

github.com/qdrant/qdrant
qdrant.tech

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

Technical documentation

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

docs.microsoft.com/en-us/azure/azure-sql

qdrant.tech/documentation

www.xtdb.com/docs

Developer

Google

Microsoft

Qdrant

Juxt Ltd.

Initial release

2014

2010

2021

2019

Current release

2.1.12, February 2017

V12

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

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++

Rust

Clojure

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

hosted

Docker
Linux
macOS
Windows

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

Numbers, Strings, Geo, Boolean

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.

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

HTTP REST
JDBC

Supported programming languages

JavaScript

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Clojure
Java

Server-side scripts

Stored procedures

Transact SQL

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with always 3 replicas available

Collection-level replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable 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, 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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

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More resources

DB-Engines blog posts

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7 February 2017, Matthias Gelbmann

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