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DBMS > Databricks vs. Lovefield vs. Oracle Berkeley DB vs. Splice Machine vs. Yaacomo

System Properties Comparison Databricks vs. Lovefield vs. Oracle Berkeley DB vs. Splice Machine vs. Yaacomo

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLovefield  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSplice Machine  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed 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.Embeddable relational database for web apps written in pure JavaScriptWidely used in-process key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational 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
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.databricks.comgoogle.github.io/­lovefieldwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsplicemachine.comyaacomo.com
Technical documentationdocs.databricks.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperDatabricksGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleSplice MachineQ2WEB GmbH
Initial release20132014199420142009
Current release2.1.12, February 201718.1.40, May 20203.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infocommercial license availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language infovia JavaScript builder patternyes infoSQL interfaced based on SQLite is availableyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesPython
R
Scala
JavaScript.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes infoJava
TriggersUsing read-only observersyes infoonly for the SQL APIyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing MemoryDByesyesyes
User concepts infoAccess controlnonoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksLovefieldOracle Berkeley DBSplice MachineYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksLovefieldOracle Berkeley DBSplice MachineYaacomo
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