DBMS > Lovefield vs. Microsoft Azure AI Search vs. Oracle vs. Sphinx vs. Warp 10

System Properties Comparison Lovefield vs. Microsoft Azure AI Search vs. Oracle vs. Sphinx vs. Warp 10

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

Widely used RDBMS

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

google.github.io/lovefield

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

www.oracle.com/database

sphinxsearch.com

www.warp10.io

Technical documentation

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

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

docs.oracle.com/en/database

sphinxsearch.com/docs

www.warp10.io/content/02_Getting_started

Developer

Google

Microsoft

Oracle

Sphinx Technologies Inc.

SenX

Initial release

2014

2015

1980

2001

2015

Current release

2.1.12, February 2017

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

Open Source

Apache License 2.0

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

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

Schemaless in JSON and XML columns

yes

schema-free

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

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol

HTTP API
Jupyter
WebSocket

Supported programming languages

JavaScript

C#
Java
JavaScript
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

yes

WarpScript

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

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

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

yes

using Azure authentication

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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