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DBMS > Hypertable vs. LMDB vs. Spark SQL

System Properties Comparison Hypertable vs. LMDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.33
Rank#118  Overall
#21  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sql
Technical documentationwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHypertable Inc.SymasApache Software Foundation
Initial release200920112014
Current release0.9.8.11, March 20160.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CScala
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes
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 indexesrestricted infoonly exact value or prefix value scansnono
SQL infoSupport of SQLnonoSQL-like DML and DDL statements
APIs and other access methodsC++ API
Thrift
JDBC
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnonono

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More resources
HypertableLMDBSpark SQL
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