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DBMS > Amazon SimpleDB vs. Databricks vs. Google Cloud Firestore vs. IBM Db2 warehouse vs. Stardog

System Properties Comparison Amazon SimpleDB vs. Databricks vs. Google Cloud Firestore vs. IBM Db2 warehouse vs. Stardog

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.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.Cloud-based data warehousing serviceEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value storeDocument store
Relational DBMS
Document storeRelational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­simpledbwww.databricks.comfirebase.google.com/­products/­firestorewww.ibm.com/­products/­db2/­warehousewww.stardog.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.databricks.comfirebase.google.com/­docs/­firestoredocs.stardog.com
DeveloperAmazonDatabricksGoogleIBMStardog-Union
Initial release20072013201720142010
Current release7.3.0, May 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial 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 serviceyesyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedhostedhostedhostedLinux
macOS
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or datenoyesyesyes
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.yesnono infoImport/export of XML data possibleno infoImport/export of XML data possible
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnowith Databricks SQLnoyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
.NET Client API
JDBC
ODBC
OLE DB
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++
Erlang
Java
PHP
Python
Ruby
Scala
Python
R
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes, Firebase Rules & Cloud FunctionsPL/SQL, SQL PLuser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes, with Cloud Functionsyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replicationyesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDyesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.fine grained access rights according to SQL-standardAccess rights for users and roles
More information provided by the system vendor
Amazon SimpleDBDatabricksGoogle Cloud FirestoreIBM Db2 warehouse infoformerly named IBM dashDBStardog
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon SimpleDBDatabricksGoogle Cloud FirestoreIBM Db2 warehouse infoformerly named IBM dashDBStardog
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