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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. InterSystems IRIS

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. InterSystems IRIS

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonInterSystems IRIS  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Cloud-based data warehousing serviceA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability
Primary database modelDocument storeTime Series DBMSKey-value store
Wide column store
Relational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Websiteaws.amazon.com/­documentdbiotdb.apache.orgcloud.google.com/­bigtablewww.ibm.com/­products/­db2/­warehousewww.intersystems.com/­products/­intersystems-iris
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­bigtable/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.cls
DeveloperApache Software FoundationGoogleIBMInterSystems
Initial release20192018201520142018
Current release1.1.0, April 20232023.3, June 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedhostedAIX
Linux
macOS
Ubuntu
Windows
Data schemeschema-freeyesschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 infoImport/export of XML data possibleyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoSQL-like query languagenoyesyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesnoPL/SQL, SQL PLyes
Triggersnoyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasInternal replication in Colossus, and regional replication between two clusters in different zonesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoAtomic single-row operationsACIDACID
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.yesnoyesyes
User concepts infoAccess controlAccess rights for users and rolesyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyes
More information provided by the system vendor
Amazon DocumentDBApache IoTDBGoogle Cloud BigtableIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRIS
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Amazon DocumentDBApache IoTDBGoogle Cloud BigtableIBM Db2 warehouse infoformerly named IBM dashDBInterSystems IRIS
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