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DBMS > Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. Apache Druid vs. Firebase Realtime Database vs. Kinetica

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. Apache Druid vs. Firebase Realtime Database vs. Kinetica

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonAmazon DocumentDB  Xexclude from comparisonApache Druid  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingFast, 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 dataCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesDocument storeRelational DBMS
Time Series DBMS
Document storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score1.91
Rank#131  Overall
#24  Document stores
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputeaws.amazon.com/­documentdbdruid.apache.orgfirebase.google.com/­products/­realtime-databasewww.kinetica.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputeaws.amazon.com/­documentdb/­resourcesdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­databasedocs.kinetica.com
DeveloperAlibabaApache Software Foundation and contributorsGoogle infoacquired by Google 2014Kinetica
Initial release20162019201220122012
Current release29.0.1, April 20247.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache license v2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++
Server operating systemshostedhostedLinux
OS X
Unix
hostedLinux
Data schemeyesschema-freeyes infoschema-less columns are supportedschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesnoyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL for queryingnoSQL-like DML and DDL statements
APIs and other access methodsFluentd
Flume
MaxCompute Console
proprietary protocol using JSON (MongoDB compatible)JDBC
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJavaGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
JavaScript
Objective-C
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin Javanonolimited functionality with using 'rules'user defined functions
TriggersnononoCallbacks are triggered when data changesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenoneSharding infomanual/auto, time-basedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, via HDFS, S3 or other storage enginesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-document operationsnoyesno
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.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyes, based on authentication and database rulesAccess rights for users and roles on table level

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More resources
Alibaba Cloud MaxComputeAmazon DocumentDBApache DruidFirebase Realtime DatabaseKinetica
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