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DBMS > Alibaba Cloud MaxCompute vs. Apache Druid vs. Google Cloud Datastore vs. Kinetica vs. Tkrzw

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Druid vs. Google Cloud Datastore vs. Kinetica vs. Tkrzw

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMS
Time Series DBMS
Document storeRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.77
Rank#214  Overall
#98  Relational DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.alibabacloud.com/­product/­maxcomputedruid.apache.orgcloud.google.com/­datastorewww.kinetica.comdbmx.net/­tkrzw
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputedruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docsdocs.kinetica.com
DeveloperAlibabaApache Software Foundation and contributorsGoogleKineticaMikio Hirabayashi
Initial release20162012200820122020
Current release29.0.1, April 20247.1, August 20210.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++
Server operating systemshostedLinux
OS X
Unix
hostedLinuxLinux
macOS
Data schemeyesyes infoschema-less columns are supportedschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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 indexesnoyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL for queryingSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJavaClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Javanousing Google App Engineuser defined functionsno
TriggersnonoCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infomanual/auto, time-basedShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes, via HDFS, S3 or other storage enginesMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate 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.Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.nononoyes infoGPU vRAM or System RAMyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelno

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More resources
Alibaba Cloud MaxComputeApache DruidGoogle Cloud DatastoreKineticaTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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