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DBMS > Databricks vs. Ehcache vs. MarkLogic vs. VoltDB

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonMarkLogic  Xexclude from comparisonVoltDB  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 optionsOperational and transactional Enterprise NoSQL databaseDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument store
Relational DBMS
Key-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
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
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitewww.databricks.comwww.ehcache.orgwww.marklogic.comwww.voltdb.com
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.marklogic.comdocs.voltdb.com
DeveloperDatabricksTerracotta Inc, owned by Software AGMarkLogic Corp.VoltDB Inc.
Initial release2013200920012010
Current release3.10.0, March 202211.0, December 202211.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial inforestricted free version is availableOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java, C++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
Linux
OS X infofor development
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infoSQL92yes infoonly a subset of SQL 99
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
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infovia XQuery or JavaScriptJava
Triggersyes infoCache Event Listenersyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta ServeryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integritynonono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACID infocan act as a resource manager in an XA/JTA transactionACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexes
User concepts infoAccess controlnoRole-based access control at the document and subdocument levelsUsers and roles with access to stored procedures
More information provided by the system vendor
DatabricksEhcacheMarkLogicVoltDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheMarkLogicVoltDB
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