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DBMS > Amazon SimpleDB vs. Apache IoTDB vs. Google Cloud Firestore vs. GridDB vs. Kinetica

System Properties Comparison Amazon SimpleDB vs. Apache IoTDB vs. Google Cloud Firestore vs. GridDB vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  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 ScioreAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkCloud 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.Scalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUs
Primary database modelKey-value storeTime Series DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­simpledbiotdb.apache.orgfirebase.google.com/­products/­firestoregriddb.netwww.kinetica.com
Technical documentationdocs.aws.amazon.com/­simpledbiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­firestoredocs.griddb.netdocs.kinetica.com
DeveloperAmazonApache Software FoundationGoogleToshiba CorporationKinetica
Initial release20072018201720132012
Current release1.1.0, April 20235.1, August 20227.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C, C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedLinuxLinux
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nononono
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyesyes
SQL infoSupport of SQLnoSQL-like query languagenoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
Native API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesyes, Firebase Rules & Cloud Functionsnouser defined functions
Triggersnoyesyes, with Cloud Functionsyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationhorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and SparkUsing Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnoyesACID at container levelno
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.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesAccess 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 can be defined per databaseAccess rights for users and roles on table level
More information provided by the system vendor
Amazon SimpleDBApache IoTDBGoogle Cloud FirestoreGridDBKinetica
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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

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More resources
Amazon SimpleDBApache IoTDBGoogle Cloud FirestoreGridDBKinetica
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