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DBMS > Databricks vs. DuckDB vs. EsgynDB vs. NSDb

System Properties Comparison Databricks vs. DuckDB vs. EsgynDB vs. NSDb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDuckDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonNSDb  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.An embeddable, in-process, column-oriented SQL OLAP RDBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSTime Series 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
Score5.61
Rank#60  Overall
#34  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Websitewww.databricks.comduckdb.orgwww.esgyn.cnnsdb.io
Technical documentationdocs.databricks.comduckdb.org/­docsnsdb.io/­Architecture
DeveloperDatabricksEsgyn
Initial release2013201820152017
Current release1.0.0, June 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaJava, Scala
Server operating systemshostedserver-lessLinuxLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, string
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 indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLyesyesSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
Supported programming languagesPython
R
Scala
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
All languages supporting JDBC/ODBC/ADO.NetJava
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava Stored Proceduresno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication between multi datacenters
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksDuckDBEsgynDBNSDb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDuckDBEsgynDBNSDb
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