DBMS > EXASOL vs. Google Cloud Firestore vs. GraphDB vs. Prometheus vs. Snowflake

System Properties Comparison EXASOL vs. Google Cloud Firestore vs. GraphDB vs. Prometheus vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Open-source Time Series DBMS and monitoring system

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

Primary database model

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

firebase.google.com/products/firestore

www.ontotext.com

prometheus.io

www.snowflake.com

Technical documentation

www.exasol.com/resources

firebase.google.com/docs/firestore

graphdb.ontotext.com/documentation

prometheus.io/docs

docs.snowflake.net/manuals/index.html

Social network pages

Developer

Exasol

Google

Ontotext

Snowflake Computing Inc.

Initial release

2000

2017

2000

2015

2014

Current release

10.4, October 2023

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

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

Server operating systems

hosted

All OS with a Java VM
Linux
OS X
Windows

Linux
Windows

hosted

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

yes

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

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.

Import of XML data possible

yes

Secondary indexes

yes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

SQL

Support of SQL

yes

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

Triggers

yes

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

by Federation

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

yes

Transaction concepts

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

ACID

yes

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

Access rights for users, groups and roles according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

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

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI
3 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.