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DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Apache IoTDB vs. etcd vs. JanusGraph

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Apache IoTDB vs. etcd vs. JanusGraph

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonAmazon Redshift  Xexclude from comparisonApache IoTDB  Xexclude from comparisonetcd  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingLarge scale data warehouse service for use with business intelligence toolsAn 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 distributed reliable key-value storeA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMSTime Series DBMSKey-value storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#209  Overall
#98  Relational DBMS
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score2.02
Rank#125  Overall
#12  Graph DBMS
Websitewww.alibabacloud.com/­product/­maxcomputeaws.amazon.com/­redshiftiotdb.apache.orgetcd.io
github.com/­etcd-io/­etcd
janusgraph.org
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputedocs.aws.amazon.com/­redshiftiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.janusgraph.org
DeveloperAlibabaAmazon (based on PostgreSQL)Apache Software FoundationLinux Foundation; originally developed as Titan by Aurelius
Initial release2016201220182017
Current release1.1.0, April 20233.4, August 20190.6.3, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaGoJava
Server operating systemshostedhostedAll OS with a Java VM (>= 1.8)FreeBSD
Linux
Windows infoexperimental
Linux
OS X
Unix
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesnorestrictedyesnoyes
SQL infoSupport of SQLSQL-like query languageyes infodoes not fully support an SQL-standardSQL-like query languagenono
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
ODBC
JDBC
Native API
gRPC
JSON over HTTP
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesJavaAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Clojure
Java
Python
Server-side scripts infoStored proceduresuser defined functions infoin Javauser defined functions infoin Pythonyesnoyes
Triggersnonoyesyes, watching key changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)yes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoIntegration with Hadoop and Sparknoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoinformational only, not enforced by the systemnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardyesnoUser authentification and security via Rexster Graph Server

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More resources
Alibaba Cloud MaxComputeAmazon RedshiftApache IoTDBetcdJanusGraph infosuccessor of Titan
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