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DBMS > Databricks vs. DuckDB vs. Hazelcast vs. NCache

System Properties Comparison Databricks vs. DuckDB vs. Hazelcast vs. NCache

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDuckDB  Xexclude from comparisonHazelcast  Xexclude from comparisonNCache  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 RDBMSA widely adopted in-memory data gridOpen-Source and Enterprise in-memory Key-Value Store
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Search engine infoUsing distributed Lucene
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
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.91
Rank#196  Overall
#29  Key-value stores
Websitewww.databricks.comduckdb.orghazelcast.comwww.alachisoft.com/­ncache
Technical documentationdocs.databricks.comduckdb.org/­docshazelcast.org/­imdg/­docswww.alachisoft.com/­resources/­docs
DeveloperDatabricksHazelcastAlachisoft
Initial release2013201820082005
Current release1.0.0, June 20245.3.6, November 20235.3.3, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoApache Version 2; commercial licenses availableOpen Source infoEnterprise Edition available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#, .NET, .NET Core, Java
Server operating systemshostedserver-lessAll OS with a Java VMLinux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counter
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.yesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query languageSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infoEvent Listeners, Executor Servicesno infosupport for stored procedures with SQL-Server CLR
Triggersnoyes infoEventsyes infoNotifications
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes infoReplicated Mapyes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedoptimistic locking and pessimistic locking
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.noyesyesyes
User concepts infoAccess controlnoRole-based access controlAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)
More information provided by the system vendor
DatabricksDuckDBHazelcastNCache
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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More resources
DatabricksDuckDBHazelcastNCache
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