DBMS > Hive vs. Lovefield vs. Microsoft Azure AI Search vs. Snowflake

System Properties Comparison Hive vs. Lovefield vs. Microsoft Azure AI Search vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable relational database for web apps written in pure JavaScript

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Vector DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

hive.apache.org

google.github.io/lovefield

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

www.snowflake.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

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

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

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

initially developed by Facebook

Google

Microsoft

Snowflake Computing Inc.

Initial release

2012

2014

2015

2014

Current release

3.1.3, April 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

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

Java

JavaScript

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC
Thrift

RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

JavaScript

C#
Java
JavaScript
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate 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

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

User concepts

Access control

Access rights for users, groups and roles

yes

using Azure authentication

Users with fine-grained authorization concept, user roles and pluggable authentication

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