DBMS > Badger vs. Fauna vs. Google Cloud Datastore vs. searchxml

System Properties Comparison Badger vs. Fauna vs. Google Cloud Datastore vs. searchxml

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Key-value store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store

Native XML DBMS
Search engine

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

github.com/dgraph-io/badger

fauna.com

cloud.google.com/datastore

www.searchxml.net/category/products

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.fauna.com

cloud.google.com/datastore/docs

www.searchxml.net/support/handouts

Developer

DGraph Labs

Fauna, Inc.

Google

informationpartners gmbh

Initial release

2017

2014

2008

2015

Current release

1.0

License

Commercial or Open Source

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

Scala

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes, details here

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 query language (GQL)

APIs and other access methods

RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

using Google App Engine

yes

on the application server

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Multi-source replication using Paxos

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

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)

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Fauna Launches Distributed Document-Relational Database On Google Cloud Marketplace
21 March 2024, GlobeNewswire

Slicing the Gordian Knot: A leap to real-time systems of truth
3 February 2024, SiliconANGLE News

Fauna Adds Groundbreaking New Database Language and Seamless Developer Experience to Enterprise Proven ...
22 August 2023, Business Wire

Fauna Query Language tamed to appeal to developers
22 August 2023, The Register

Utah Natural Heritage Program
17 October 2023, Utah Division of Wildlife Resources

provided by Google News

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
29 April 2024, TechRadar

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

What is Google App Engine? | Definition from TechTarget
26 April 2024, TechTarget

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

provided by Google News

Share this page