DBMS > Fauna vs. GeoSpock vs. Microsoft Azure Cosmos DB vs. Splunk

System Properties Comparison Fauna vs. GeoSpock vs. Microsoft Azure Cosmos DB vs. Splunk

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

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.

Spatial and temporal data processing engine for extreme data scale

Globally distributed, horizontally scalable, multi-model database service

Analytics Platform for Big Data

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Secondary database models

Time Series DBMS

Spatial DBMS

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

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

fauna.com

geospock.com

azure.microsoft.com/services/cosmos-db

www.splunk.com

Technical documentation

docs.fauna.com

learn.microsoft.com/azure/cosmos-db

docs.splunk.com/Documentation/Splunk

Developer

Fauna, Inc.

GeoSpock

Microsoft

Splunk Inc.

Initial release

2014

2003

Current release

2.0, September 2019

License

Commercial or Open Source

commercial

Limited free edition and free developer edition available

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

Java, Javascript

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

temporal, categorical

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP API

JDBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Automatic sharding

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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 can be defined per table

Access rights can be defined down to the item level

Access rights for users and roles

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