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DBMS > Amazon DocumentDB vs. Hawkular Metrics vs. Manticore Search vs. Solr

System Properties Comparison Amazon DocumentDB vs. Hawkular Metrics vs. Manticore Search vs. Solr

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonManticore Search  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHawkular 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.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeTime Series DBMSSearch engineSearch engine
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibrarySpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score0.23
Rank#317  Overall
#21  Search engines
Score44.28
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbwww.hawkular.orgmanticoresearch.comsolr.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourceswww.hawkular.org/­hawkular-metrics/­docs/­user-guidemanual.manticoresearch.comsolr.apache.org/­resources.html
DeveloperCommunity supported by Red HatManticore SoftwareApache Software Foundation
Initial release2019201420172006
Current release6.0, February 20239.5.0, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPL version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemshostedLinux
OS X
Windows
FreeBSD
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeFixed schemayes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infosupports customizable data types and automatic typing
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.nonoCan index from XMLyes
Secondary indexesyesnoyes infofull-text index on all search fieldsyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HTTP RESTBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Go
Java
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonouser defined functionsJava plugins
Triggersnoyes infovia Hawkular Alertingnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factor infobased on CassandraSynchronous replication based on Galera libraryyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoyes infoisolated transactions for atomic changes and binary logging for safe writesoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.noyes
User concepts infoAccess controlAccess rights for users and rolesnonoyes

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More resources
Amazon DocumentDBHawkular MetricsManticore SearchSolr
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