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DBMS > Databricks vs. Ehcache vs. LMDB vs. MarkLogic

System Properties Comparison Databricks vs. Ehcache vs. LMDB vs. MarkLogic

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonLMDB  Xexclude from comparisonMarkLogic  Xexclude from comparison
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.A widely adopted Java cache with tiered storage optionsA high performant, light-weight, embedded key-value database libraryOperational and transactional Enterprise NoSQL database
Primary database modelDocument store
Relational DBMS
Key-value storeKey-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score2.09
Rank#121  Overall
#20  Key-value stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Websitewww.databricks.comwww.ehcache.orgwww.symas.com/­symas-embedded-database-lmdbwww.progress.com/­marklogic
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationwww.lmdb.tech/­docwww.progress.com/­marklogic/­documentation
DeveloperDatabricksTerracotta Inc, owned by Software AGSymasMarkLogic Corp.
Initial release2013200920112001
Current release3.10.0, March 20220.9.32, January 202411.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Sourcecommercial inforestricted free version is 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 languageJavaCC++
Server operating systemshostedAll OS with a Java VMLinux
Unix
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyes
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.yesnonoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLnonoyes infoSQL92
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languagesPython
R
Scala
Java.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
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes infovia XQuery or JavaScript
Triggersyes infoCache Event Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServernoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Servernoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACIDACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes, with Range Indexes
User concepts infoAccess controlnonoRole-based access control at the document and subdocument levels
More information provided by the system vendor
DatabricksEhcacheLMDBMarkLogic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheLMDBMarkLogic
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