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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. Google Cloud Bigtable vs. Netezza

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. Google Cloud Bigtable vs. Netezza

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.Data warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument storeTime Series DBMSKey-value store
Wide column store
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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteaws.amazon.com/­documentdbiotdb.apache.orgcloud.google.com/­bigtablewww.ibm.com/­products/­netezza
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­bigtable/­docs
DeveloperApache Software FoundationGoogleIBM
Initial release2019201820152000
Current release1.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedLinux infoincluded in appliance
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoSQL-like query languagenoyes
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)
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoyesnoyes
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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 zonesSource-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 Sparkyesyes
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)
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and rolesyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept

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More resources
Amazon DocumentDBApache IoTDBGoogle Cloud BigtableNetezza infoAlso called PureData System for Analytics by IBM
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