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DBMS > Databricks vs. Ehcache vs. GBase vs. Heroic

System Properties Comparison Databricks vs. Ehcache vs. GBase vs. Heroic

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonGBase  Xexclude from comparisonHeroic  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 optionsWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSTime Series 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
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Websitewww.databricks.comwww.ehcache.orgwww.gbase.cngithub.com/­spotify/­heroic
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationspotify.github.io/­heroic
DeveloperDatabricksTerracotta Inc, owned by Software AGGeneral Data Technology Co., Ltd.Spotify
Initial release2013200920042014
Current release3.10.0, March 2022GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen 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 languageJavaC, Java, PythonJava
Server operating systemshostedAll OS with a Java VMLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
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.yesnoyesno
Secondary indexesyesnoyesyes infovia Elasticsearch
SQL infoSupport of SQLwith Databricks SQLnoStandard with numerous extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheADO.NET
C API
JDBC
ODBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesPython
R
Scala
JavaC#
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functionsno
Triggersyes infoCache Event Listenersyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta Serverhorizontal partitioning (by range, list and hash) and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serveryesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyEventual Consistency
Immediate 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 resourceACIDno
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.noyesno
User concepts infoAccess controlnoyes
More information provided by the system vendor
DatabricksEhcacheGBaseHeroic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheGBaseHeroic
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