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DBMS > Databricks vs. Ehcache vs. TimescaleDB vs. YDB

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYDB  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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelDocument store
Relational DBMS
Key-value storeTime Series DBMSDocument store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score4.79
Rank#66  Overall
#8  Key-value stores
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Score0.39
Rank#269  Overall
#43  Document stores
#126  Relational DBMS
Websitewww.databricks.comwww.ehcache.orgwww.timescale.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.timescale.comydb.tech/­en/­docs
DeveloperDatabricksTerracotta Inc, owned by Software AGTimescaleYandex
Initial release2013200920172019
Current release3.10.0, March 20222.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoApache 2.0; commercial license 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 languageJavaC
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.yesnoyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infofull PostgreSQL SQL syntaxSQL-like query language (YQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesPython
R
Scala
Java.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersyes infoCache Event Listenersyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta Serveryes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta ServerSource-replica replication with hot standby and reads on replicas infoActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
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 approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users
More information provided by the system vendor
DatabricksEhcacheTimescaleDBYDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEhcacheTimescaleDBYDB
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