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DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. Hawkular Metrics vs. Manticore Search vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. Hawkular Metrics vs. Manticore Search vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonManticore Search  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Multi-storage database for search, including full-text search.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeDocument store
Key-value store
Time Series DBMSSearch engineRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.hawkular.orgmanticoresearch.comsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.hawkular.org/­hawkular-metrics/­docs/­user-guidemanual.manticoresearch.comsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsCommunity supported by Red HatManticore SoftwareSplice Machine
Initial release20192016201420172014
Current release17036.0, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2Open Source infoAGPL 3.0, commercial license available
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 languageJavaJavaC++Java
Server operating systemshostedLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeSchema and schema-less with LDAP viewsschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyesoptionalyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.noyesnoCan index from XML
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnononoSQL-like query languageyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)LDAPHTTP RESTBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages with LDAP bindingsGo
Java
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononouser defined functionsyes infoJava
Triggersnoyesyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesselectable replication factor infobased on CassandraSynchronous replication based on Galera libraryMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic execution of specific operationsnoyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesLDAP bind authenticationnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBAtos Standard Common RepositoryHawkular MetricsManticore SearchSplice Machine
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