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DBMS > Amazon DocumentDB vs. Graphite vs. Hawkular Metrics vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Graphite vs. Hawkular Metrics vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGraphite  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeTime Series DBMSTime Series DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­graphite-project/­graphite-webwww.hawkular.orgsphinxsearch.comsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesgraphite.readthedocs.iowww.hawkular.org/­hawkular-metrics/­docs/­user-guidesphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperChris DavisCommunity supported by Red HatSphinx Technologies Inc.Splice Machine
Initial release20192006201420012014
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonJavaC++Java
Server operating systemshostedLinux
Unix
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesnoyes
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.nonono
Secondary indexesyesnonoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HTTP API
Sockets
HTTP RESTProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonononoyes infoJava
Triggersnonoyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding 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 replicasnoneselectable replication factor infobased on CassandranoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual 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 operationsnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx 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 rolesnononoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBGraphiteHawkular MetricsSphinxSplice Machine
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