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DBMS > Databricks vs. Hypertable vs. IRONdb vs. Sphinx

System Properties Comparison Databricks vs. Hypertable vs. IRONdb vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHypertable  Xexclude from comparisonIRONdb  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.An open source BigTable implementation based on distributed file systems such as HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Wide column storeTime Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitewww.databricks.comwww.circonus.com/solutions/time-series-database/sphinxsearch.com
Technical documentationdocs.databricks.comdocs.circonus.com/irondb/category/getting-startedsphinxsearch.com/­docs
DeveloperDatabricksHypertable Inc.Circonus LLC.Sphinx Technologies Inc.
Initial release2013200920172001
Current release0.9.8.11, March 2016V0.10.20, January 20183.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoGPL version 2, commercial licence available
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 languageC++C and C++C++
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes infotext, numeric, histogramsno
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.yesno
Secondary indexesyesrestricted infoonly exact value or prefix value scansnoyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
C++ API
Thrift
HTTP APIProprietary protocol
Supported programming languagesPython
R
Scala
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes, in Luano
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor on file system levelconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nono
User concepts infoAccess controlnonono
More information provided by the system vendor
DatabricksHypertableIRONdbSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHypertableIRONdbSphinx
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