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DBMS > Alibaba Cloud MaxCompute vs. Apache IoTDB vs. Google Cloud Bigtable vs. OrigoDB vs. YottaDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache IoTDB vs. Google Cloud Bigtable vs. OrigoDB vs. YottaDB

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOrigoDB  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingAn 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.A fully ACID in-memory object graph databaseA fast and solid embedded Key-value store
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesTime Series DBMSKey-value store
Wide column store
Document store
Object oriented DBMS
Key-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitewww.alibabacloud.com/­product/­maxcomputeiotdb.apache.orgcloud.google.com/­bigtableorigodb.comyottadb.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputeiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­bigtable/­docsorigodb.com/­docsyottadb.com/­resources/­documentation
DeveloperAlibabaApache Software FoundationGoogleRobert Friberg et alYottaDB, LLC
Initial release2016201820152009 infounder the name LiveDB2001
Current release1.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoAGPL 3.0
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
Server operating systemshostedAll OS with a Java VM (>= 1.8)hostedLinux
Windows
Docker
Linux
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoUser defined using .NET types and collectionsno
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 infocan be achieved using .NETno
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languagenonoby using the Octo plugin
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
Native API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
HTTP API
LINQ
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesJavaC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.NetC
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresuser defined functions infoin Javayesnoyes
Triggersnoyesnoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceselectable 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 replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesIntegration with Hadoop and Sparkyesnono
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 integritynononodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic single-row operationsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesyes
User concepts infoAccess controlAccess rights for users and rolesyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based authorizationUsers and groups based on OS-security mechanisms

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More resources
Alibaba Cloud MaxComputeApache IoTDBGoogle Cloud BigtableOrigoDBYottaDB
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