DBMS > Fauna vs. Google Cloud Datastore vs. Lovefield vs. Microsoft Azure Search

System Properties Comparison Fauna vs. Google Cloud Datastore vs. Lovefield vs. Microsoft Azure Search

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Editorial information provided by DB-Engines
Name	Fauna previously named FaunaDB  Xexclude from comparison	Google Cloud Datastore  Xexclude from comparison	Lovefield  Xexclude from comparison	Microsoft Azure Search  Xexclude from comparison
Description	Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.	Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform	Embeddable relational database for web apps written in pure JavaScript	Search-as-a-service for web and mobile app development
Primary database model	Document store Graph DBMS Relational DBMS Time Series DBMS	Document store	Relational DBMS	Search engine
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 1.33 Rank #148   Overall #25   Document stores #12   Graph DBMS #71   Relational DBMS #10   Time Series DBMS	Score 5.89 Rank #71   Overall #12   Document stores	Score 0.23 Rank #286   Overall #134   Relational DBMS	Score 7.61 Rank #58   Overall #6   Search engines
Website	fauna.com	cloud.google.com/­datastore	google.github.io/­lovefield	azure.microsoft.com/­en-us/­services/­search
Technical documentation	docs.fauna.com	cloud.google.com/­datastore/­docs	github.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md	docs.microsoft.com/­en-us/­azure/­search
Developer	Fauna, Inc.	Google	Google	Microsoft
Initial release	2014	2008	2014	2015
Current release			2.1.12, February 2017	V1
License Commercial or Open Source	commercial	commercial	Open Source Apache 2.0	commercial
Cloud-based only Only available as a cloud service	yes	yes	no	yes
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Scala		JavaScript
Server operating systems	hosted	hosted	server-less, requires a JavaScript environment (browser, Node.js) tested with Chrome, Firefox, IE, Safari	hosted
Data scheme	schema-free	schema-free	yes	yes
Typing predefined data types such as float or date	no	yes, details here	yes	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.	no	no	no	no
Secondary indexes	yes	yes	yes	yes
SQL Support of SQL	no	SQL-like query language (GQL)	SQL-like query language via JavaScript builder pattern	no
APIs and other access methods	RESTful HTTP API	gRPC (using protocol buffers) API RESTful HTTP/JSON API		RESTful HTTP API
Supported programming languages	C# Go Java JavaScript Python Ruby Scala Swift	.Net Go Java JavaScript (Node.js) PHP Python Ruby	JavaScript	.Net C#
Server-side scripts Stored procedures	user defined functions	using Google App Engine	no	no
Triggers	no	Callbacks using the Google Apps Engine	Using read-only observers	no
Partitioning methods Methods for storing different data on different nodes	horizontal partitioning consistent hashing	Sharding	none	Sharding Implicit feature of the cloud service
Replication methods Methods for redundantly storing data on multiple nodes	Multi-source replication	Multi-source replication using Paxos	none	yes Implicit feature of the cloud service
MapReduce Offers an API for user-defined Map/Reduce methods	no	yes using Google Cloud Dataflow	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency	Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.		Immediate Consistency
Foreign keys Referential integrity	yes	yes via ReferenceProperties or Ancestor paths	yes	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	ACID	ACID Serializable Isolation within Transactions, Read Committed outside of Transactions	ACID	no
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	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.	no	no	yes using MemoryDB	no
User concepts Access control	Identity management, authentication, and access control	Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	no	yes using Azure authentication
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More resources
	Fauna previously named FaunaDB	Google Cloud Datastore	Lovefield	Microsoft Azure Search
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