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DBMS > Amazon DocumentDB vs. Apache Druid vs. Apache IoTDB vs. Hypertable vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. Apache IoTDB vs. Hypertable vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHypertable  Xexclude from comparisonYaacomo  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAn open source BigTable implementation based on distributed file systems such as HadoopOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeRelational DBMS
Time Series DBMS
Time Series DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Websiteaws.amazon.com/­documentdbdruid.apache.orgiotdb.apache.orgyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.html
DeveloperApache Software Foundation and contributorsApache Software FoundationHypertable Inc.Q2WEB GmbH
Initial release20192012201820092009
Current release29.0.1, April 20241.1.0, April 20230.9.8.11, March 2016
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemshostedLinux
OS X
Unix
All OS with a Java VM (>= 1.8)Linux
OS X
Windows infoan inofficial Windows port is available
Android
Linux
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnoSQL for queryingSQL-like query languagenoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
RESTful HTTP/JSON API
JDBC
Native API
C++ API
Thrift
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnononoACID
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 rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesnofine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBApache DruidApache IoTDBHypertableYaacomo
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