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DBMS > Alibaba Cloud MaxCompute vs. Apache Phoenix vs. Google Cloud Bigtable vs. Kinetica

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Phoenix vs. Google Cloud Bigtable vs. Kinetica

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Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Bigtable  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 warehousingA scale-out RDBMS with evolutionary schema built on Apache HBaseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMSKey-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.54
Rank#237  Overall
#113  Relational DBMS
Score3.16
Rank#103  Overall
#52  Relational DBMS
Score5.03
Rank#79  Overall
#12  Key-value stores
#6  Wide column stores
Score0.47
Rank#246  Overall
#117  Relational DBMS
Websitewww.alibabacloud.com/­product/­maxcomputephoenix.apache.orgcloud.google.com/­bigtablewww.kinetica.com
Technical documentationwww.alibabacloud.com/­help/­product/­27797.htmphoenix.apache.orgcloud.google.com/­bigtable/­docswww.kinetica.com/­docs
DeveloperAlibabaApache Software FoundationGoogleKinetica
Initial release2016201420152012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.1, August 2021
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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++
Server operating systemshostedLinux
Unix
Windows
hostedLinux
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-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.nononono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like DML and DDL statements
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJavaC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functionsnouser defined functions
Triggersnononoyes 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 serviceShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsno
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.noyesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level
More information provided by the system vendor
Alibaba Cloud MaxComputeApache PhoenixGoogle Cloud BigtableKinetica
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more
Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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More resources
Alibaba Cloud MaxComputeApache PhoenixGoogle Cloud BigtableKinetica
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