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DBMS > Alibaba Cloud MaxCompute vs. Apache Impala vs. Datomic vs. JanusGraph vs. NSDb

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Impala vs. Datomic vs. JanusGraph vs. NSDb

Editorial information provided by DB-Engines
NameAlibaba Cloud MaxCompute  Xexclude from comparisonApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionMaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousingAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelRelational DBMS infoa graph-processing framework is available with the graphs being stored in tablesRelational DBMSRelational DBMSGraph DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.77
Rank#214  Overall
#98  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websitewww.alibabacloud.com/­product/­maxcomputeimpala.apache.orgwww.datomic.comjanusgraph.orgnsdb.io
Technical documentationwww.alibabacloud.com/­help/­en/­maxcomputeimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.janusgraph.orgnsdb.io/­Architecture
DeveloperAlibabaApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectLinux Foundation; originally developed as Titan by Aurelius
Initial release20162013201220172017
Current release4.1.0, June 20221.0.6735, June 20230.6.3, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infolimited edition freeOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, ClojureJavaJava, Scala
Server operating systemshostedLinuxAll OS with a Java VMLinux
OS X
Unix
Windows
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes: int, bigint, decimal, string
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 indexesnoyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnonoSQL-like query language
APIs and other access methodsFluentd
Flume
MaxCompute Console
JDBC
ODBC
RESTful HTTP APIJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
gRPC
HTTP REST
WebSocket
Supported programming languagesJavaAll languages supporting JDBC/ODBCClojure
Java
Clojure
Java
Python
Java
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Javayes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyesno
TriggersnonoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingnone infoBut extensive use of caching in the application peersyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceselectable replication factornone infoBut extensive use of caching in the application peersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, HazelcastUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and development
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUser authentification and security via Rexster Graph Server

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More resources
Alibaba Cloud MaxComputeApache ImpalaDatomicJanusGraph infosuccessor of TitanNSDb
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