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DBMS > DuckDB vs. Hypertable vs. KeyDB vs. Sphinx

System Properties Comparison DuckDB vs. Hypertable vs. KeyDB vs. Sphinx

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Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonHypertable  Xexclude from comparisonKeyDB  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSAn open source BigTable implementation based on distributed file systems such as HadoopAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeKey-value storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.61
Rank#60  Overall
#34  Relational DBMS
Score0.63
Rank#232  Overall
#32  Key-value stores
Score5.97
Rank#56  Overall
#5  Search engines
Websiteduckdb.orggithub.com/­Snapchat/­KeyDB
keydb.dev
sphinxsearch.com
Technical documentationduckdb.org/­docsdocs.keydb.devsphinxsearch.com/­docs
DeveloperHypertable Inc.EQ Alpha Technology Ltd.Sphinx Technologies Inc.
Initial release2018200920192001
Current release1.0.0, June 20240.9.8.11, March 20163.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoGNU version 3. Commercial license availableOpen Source infoBSD-3Open 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 languageC++C++C++C++
Server operating systemsserver-lessLinux
OS X
Windows infoan inofficial Windows port is available
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesno
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 indexesyesrestricted infoonly exact value or prefix value scansyes infoby using the Redis Search moduleyes infofull-text index on all search fields
SQL infoSupport of SQLyesnonoSQL-like query language (SphinxQL)
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
C++ API
Thrift
Proprietary protocol infoRESP - REdis Serialization ProtocoProprietary protocol
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoLuano
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor on file system levelMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoOptimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes 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.yesyes
User concepts infoAccess controlnonosimple password-based access control and ACLno

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