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

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

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonIgnite  Xexclude from comparisonManticore Search  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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Multi-storage database for search, including full-text search.
Primary database modelDocument storeTime Series DBMSKey-value store
Relational DBMS
Search engine
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
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
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score0.23
Rank#317  Overall
#21  Search engines
Websiteaws.amazon.com/­documentdbwww.hawkular.orgignite.apache.orgmanticoresearch.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.hawkular.org/­hawkular-metrics/­docs/­user-guideapacheignite.readme.io/­docsmanual.manticoresearch.com
DeveloperCommunity supported by Red HatApache Software FoundationManticore Software
Initial release2019201420152017
Current releaseApache Ignite 2.66.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPL 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, .NetC++
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Windows
Data schemeschema-freeschema-freeyesFixed schema
Typing infopredefined data types such as float or dateyesyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.nonoyesCan index from XML
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoANSI-99 for query and DML statements, subset of DDLSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HTTP RESTHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Go
Java
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersnoyes infovia Hawkular Alertingyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
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 Cassandrayes (replicated cache)Synchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate 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 operationsnoACIDyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
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 rolesnoSecurity Hooks for custom implementationsno

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More resources
Amazon DocumentDBHawkular MetricsIgniteManticore Search
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