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DBMS > Databricks vs. DuckDB vs. Netezza vs. Sqrrl

System Properties Comparison Databricks vs. DuckDB vs. Netezza vs. Sqrrl

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDuckDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed 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.An embeddable, in-process, column-oriented SQL OLAP RDBMSData warehouse and analytics appliance part of IBM PureSystemsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column 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
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitewww.databricks.comduckdb.orgwww.ibm.com/­products/­netezzasqrrl.com
Technical documentationdocs.databricks.comduckdb.org/­docs
DeveloperDatabricksIBMAmazon infooriginally Sqrrl Data, Inc.
Initial release2013201820002012
Current release1.0.0, June 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedserver-lessLinux infoincluded in applianceLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-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.yesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JDBC
ODBC
OLE DB
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
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
C
C++
Fortran
Java
Lua
Perl
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replicationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyes
User concepts infoAccess controlnoUsers with fine-grained authorization conceptCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
DatabricksDuckDBNetezza infoAlso called PureData System for Analytics by IBMSqrrl
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDuckDBNetezza infoAlso called PureData System for Analytics by IBMSqrrl
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