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DBMS > Apache IoTDB vs. Google Cloud Datastore vs. Graph Engine vs. Heroic vs. Oracle Rdb

System Properties Comparison Apache IoTDB vs. Google Cloud Datastore vs. Graph Engine vs. Heroic vs. Oracle Rdb

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHeroic  Xexclude from comparisonOracle Rdb  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelTime Series DBMSDocument storeGraph DBMS
Key-value store
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score1.14
Rank#178  Overall
#80  Relational DBMS
Websiteiotdb.apache.orgcloud.google.com/­datastorewww.graphengine.iogithub.com/­spotify/­heroicwww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­datastore/­docswww.graphengine.io/­docs/­manualspotify.github.io/­heroicwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperApache Software FoundationGoogleMicrosoftSpotifyOracle, originally developed by Digital Equipment Corporation (DEC)
Initial release20182008201020141984
Current release1.1.0, April 20237.4.1.1, 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT LicenseOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and CJava
Server operating systemsAll OS with a Java VM (>= 1.8)hosted.NETHP Open VMS
Data schemeyesschema-freeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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.nonononono
Secondary indexesyesyesyes infovia Elasticsearchyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (GQL)nonoyes
APIs and other access methodsJDBC
Native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
Server-side scripts infoStored proceduresyesusing Google App Engineyesno
TriggersyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnonoyes, on a single node
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnono
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache IoTDBGoogle Cloud DatastoreGraph Engine infoformer name: TrinityHeroicOracle Rdb
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