DBMS > Fauna vs. GridGain vs. Prometheus vs. SAP HANA

System Properties Comparison Fauna vs. GridGain vs. Prometheus vs. SAP HANA

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Editorial information provided by DB-Engines

Name

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.

GridGain is an in-memory computing platform, built on Apache Ignite

Open-source Time Series DBMS and monitoring system

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

fauna.com

www.gridgain.com

prometheus.io

www.sap.com/products/hana.html

Technical documentation

docs.fauna.com

www.gridgain.com/docs/index.html

prometheus.io/docs

help.sap.com/hana

Developer

Fauna, Inc.

GridGain Systems, Inc.

SAP

Initial release

2014

2007

2015

2010

Current release

GridGain 8.5.1

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Java, C++, .Net

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

SQLScript, R

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes (replicated cache)

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

Security Hooks for custom implementations

yes

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