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DBMS > BoltDB vs. Databricks vs. Heroic vs. Spark SQL

System Properties Comparison BoltDB vs. Databricks vs. Heroic vs. Spark SQL

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDatabricks  Xexclude from comparisonHeroic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embedded key-value store for Go.The 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 ElasticSearchSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Relational DBMS
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­boltdb/­boltwww.databricks.comgithub.com/­spotify/­heroicspark.apache.org/­sql
Technical documentationdocs.databricks.comspotify.github.io/­heroicspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksSpotifyApache Software Foundation
Initial release2013201320142014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyesyes
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.noyesnono
Secondary indexesnoyesyes infovia Elasticsearchno
SQL infoSupport of SQLnowith Databricks SQLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Supported programming languagesGoPython
R
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnono
More information provided by the system vendor
BoltDBDatabricksHeroicSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BoltDBDatabricksHeroicSpark SQL
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