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DBMS > HarperDB vs. Hawkular Metrics vs. Hypertable vs. Sphinx

System Properties Comparison HarperDB vs. Hawkular Metrics vs. Hypertable vs. Sphinx

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Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHypertable  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An open source BigTable implementation based on distributed file systems such as HadoopOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeTime Series DBMSWide column storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#244  Overall
#38  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.harperdb.iowww.hawkular.orgsphinxsearch.com
Technical documentationdocs.harperdb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidesphinxsearch.com/­docs
DeveloperHarperDBCommunity supported by Red HatHypertable Inc.Sphinx Technologies Inc.
Initial release2017201420092001
Current release3.1, August 20210.9.8.11, March 20163.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache 2.0Open Source infoGNU version 3. Commercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsJavaC++C++
Server operating systemsLinux
OS X
Linux
OS X
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemedynamic schemaschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infoJSON data typesyesnono
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.nono
Secondary indexesyesnorestricted infoonly exact value or prefix value scansyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like data manipulation statementsnonoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP RESTC++ API
Thrift
Proprietary protocol
Supported programming languages.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Go
Java
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1nonono
Triggersnoyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterSharding infobased on CassandraShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedselectable replication factor infobased on Cassandraselectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and rolesnonono

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More resources
HarperDBHawkular MetricsHypertableSphinx
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