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DBMS > Databricks vs. EsgynDB vs. Spark SQL vs. ToroDB

System Properties Comparison Databricks vs. EsgynDB vs. Spark SQL vs. ToroDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSpark SQL is a component on top of 'Spark Core' for structured data processingA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comwww.esgyn.cnspark.apache.org/­sqlgithub.com/­torodb/­server
Technical documentationdocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksEsgynApache Software Foundation8Kdata
Initial release2013201520142016
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaScalaJava
Server operating systemshostedLinuxLinux
OS X
Windows
All OS with a Java 7 VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, boolean, date, object_id
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 indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users and roles
More information provided by the system vendor
DatabricksEsgynDBSpark SQLToroDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEsgynDBSpark SQLToroDB
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