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DBMS > Databricks vs. Ehcache vs. JanusGraph vs. TimescaleDB

System Properties Comparison Databricks vs. Ehcache vs. JanusGraph vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonTimescaleDB  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 Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Key-value storeGraph DBMSTime Series DBMS
Secondary database modelsRelational 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
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.databricks.comwww.ehcache.orgjanusgraph.orgwww.timescale.com
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.janusgraph.orgdocs.timescale.com
DeveloperDatabricksTerracotta Inc, owned by Software AGLinux Foundation; originally developed as Titan by AureliusTimescale
Initial release2013200920172017
Current release3.10.0, March 20220.6.3, February 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemshostedAll OS with a Java VMLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
JavaClojure
Java
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infoCache Event Listenersyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta Serveryes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta ServeryesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksEhcacheJanusGraph infosuccessor of TitanTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheJanusGraph infosuccessor of TitanTimescaleDB
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