DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > eXtremeDB vs. Google Cloud Firestore vs. Stardog

System Properties Comparison eXtremeDB vs. Google Cloud Firestore vs. Stardog

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringCloud 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 Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMS
Time Series DBMS
Document storeGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.mcobject.comfirebase.google.com/­products/­firestorewww.stardog.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmfirebase.google.com/­docs/­firestoredocs.stardog.com
DeveloperMcObjectGoogleStardog-Union
Initial release200120172010
Current release8.2, 20217.3.0, May 2020
License infoCommercial or Open Sourcecommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++Java
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
macOS
Windows
Data schemeyesschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no infosupport of XML interfaces availablenono infoImport/export of XML data possible
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesyes, Firebase Rules & Cloud Functionsuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infoby defining eventsyes, with Cloud Functionsyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and roles
More information provided by the system vendor
eXtremeDBGoogle Cloud FirestoreStardog
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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
eXtremeDBGoogle Cloud FirestoreStardog
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

McObject Announces the Release of eXtremeDB/rt 1.2
23 May 2023, Embedded Computing Design

McObject Offers eXtremeDB 8.3 for Incremental Improvements and New Platforms
11 November 2022, Automation.com

With eXtremeDB Database, Spreadbrokers Targets Real-Time Trading
27 March 2012, GlobeNewswire

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

Beta tests for real time in-memory embedded database ...
4 May 2021, eeNews Europe

provided by Google News

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google’s Firebase gets AI extensions, opens up its marketplace
10 May 2023, TechCrunch

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here