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

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

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonApache IoTDB  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOrigoDB  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 FlinkA widely adopted Java cache with tiered storage optionsGoogle'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 database
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesTime Series DBMSKey-value storeKey-value store
Wide column store
Document store
Object oriented DBMS
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
Score4.64
Rank#68  Overall
#8  Key-value stores
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
Websitewww.alibabacloud.com/­product/­maxcomputeiotdb.apache.orgwww.ehcache.orgcloud.google.com/­bigtableorigodb.com
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputeiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ehcache.org/­documentationcloud.google.com/­bigtable/­docsorigodb.com/­docs
DeveloperAlibabaApache Software FoundationTerracotta Inc, owned by Software AGGoogleRobert Friberg et al
Initial release20162018200920152009 infounder the name LiveDB
Current release1.1.0, April 20233.10.0, March 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC#
Server operating systemshostedAll OS with a Java VM (>= 1.8)All OS with a Java VMhostedLinux
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoUser defined using .NET types and collections
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 infocan be achieved using .NET
Secondary indexesnoyesnonoyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languagenonono
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
Native API
JCachegRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
HTTP API
LINQ
Supported programming languagesJavaC
C#
C++
Go
Java
Python
Scala
JavaC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Server-side scripts infoStored proceduresuser defined functions infoin Javayesnonoyes
Triggersnoyesyes infoCache Event Listenersnoyes 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)Sharding infoby using Terracotta ServerShardinghorizontal 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 replicasyes infoby using Terracotta ServerInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Tunable Consistency (Strong, Eventual, Weak)Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonononodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyes infosupports JTA and can work as an XA resourceAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing a tiered cache-storage approachyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes
User concepts infoAccess controlAccess rights for users and rolesyesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based authorization

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More resources
Alibaba Cloud MaxComputeApache IoTDBEhcacheGoogle Cloud BigtableOrigoDB
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