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DBMS > Databricks vs. Heroic vs. LevelDB vs. SwayDB

System Properties Comparison Databricks vs. Heroic vs. LevelDB vs. SwayDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHeroic  Xexclude from comparisonLevelDB  Xexclude from comparisonSwayDB  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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument store
Relational DBMS
Time Series DBMSKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitewww.databricks.comgithub.com/­spotify/­heroicgithub.com/­google/­leveldbswaydb.simer.au
Technical documentationdocs.databricks.comspotify.github.io/­heroicgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDatabricksSpotifyGoogleSimer Plaha
Initial release2013201420112018
Current release1.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoBSDOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Scala
Server operating systemshostedIllumos
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnono
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.yesnonono
Secondary indexesyesyes infovia Elasticsearchnono
SQL infoSupport of SQLwith Databricks SQLnonono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesPython
R
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
Kotlin
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnono
More information provided by the system vendor
DatabricksHeroicLevelDBSwayDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHeroicLevelDBSwayDB
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