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DBMS > EJDB vs. Google Cloud Firestore vs. GridGain vs. Microsoft Azure Data Explorer vs. Stardog

System Properties Comparison EJDB vs. Google Cloud Firestore vs. GridGain vs. Microsoft Azure Data Explorer vs. Stardog

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)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.GridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platformEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument storeDocument storeKey-value store
Relational DBMS
Relational DBMS infocolumn orientedGraph DBMS
RDF store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score7.36
Rank#53  Overall
#9  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitegithub.com/­Softmotions/­ejdbfirebase.google.com/­products/­firestorewww.gridgain.comazure.microsoft.com/­services/­data-explorerwww.stardog.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdfirebase.google.com/­docs/­firestorewww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.stardog.com
DeveloperSoftmotionsGoogleGridGain Systems, Inc.MicrosoftStardog-Union
Initial release20122017200720192010
Current releaseGridGain 8.5.1cloud service with continuous releases7.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercialcommercialcommercial 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 servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava, C++, .NetJava
Server operating systemsserver-lesshostedLinux
OS X
Solaris
Windows
hostedLinux
macOS
Windows
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noyesyesno infoImport/export of XML data possible
Secondary indexesnoyesyesall fields are automatically indexedyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnonoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsin-process shared libraryAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
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 languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Ruser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes, with Cloud Functionsyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Security Hooks for custom implementationsAzure Active Directory AuthenticationAccess rights for users and roles

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More resources
EJDBGoogle Cloud FirestoreGridGainMicrosoft Azure Data ExplorerStardog
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