DBMS > Lovefield vs. Microsoft Azure AI Search vs. Postgres-XL vs. TerarkDB vs. Typesense

System Properties Comparison Lovefield vs. Microsoft Azure AI Search vs. Postgres-XL vs. TerarkDB vs. Typesense

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Search-as-a-service for web and mobile app development

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Secondary database models

Vector DBMS

Document store
Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.76
Rank	#219	Overall
	#14	Search engines

Website

google.github.io/lovefield

azure.microsoft.com/en-us/services/search

www.postgres-xl.org

github.com/bytedance/terarkdb

typesense.org

Technical documentation

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

learn.microsoft.com/en-us/azure/search

www.postgres-xl.org/documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

typesense.org/docs

Developer

Google

Microsoft

ByteDance, originally Terark

Initial release

2014

2015

2014

since 2012, originally named StormDB

2016

2015

Current release

2.1.12, February 2017

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

commercial

restricted open source version available

Open Source

GPL V3

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++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

hosted

Linux
macOS

Linux

Data scheme

yes

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

C++ API
Java API

RESTful HTTP API

Supported programming languages

JavaScript

C#
Java
JavaScript
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

user defined functions

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

Multi-source replication using RAFT

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

Transaction concepts

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

ACID

MVCC

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

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

yes

using Azure authentication

fine grained access rights according to SQL-standard

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