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DBMS > Databricks vs. Hazelcast vs. Kinetica vs. NCache

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHazelcast  Xexclude from comparisonKinetica  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.A widely adopted in-memory data gridFully vectorized database across both GPUs and CPUsOpen-Source and Enterprise in-memory Key-Value Store
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
Document store
Search engine infoUsing distributed Lucene
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.96
Rank#195  Overall
#29  Key-value stores
Websitewww.databricks.comhazelcast.comwww.kinetica.comwww.alachisoft.com/­ncache
Technical documentationdocs.databricks.comhazelcast.org/­imdg/­docsdocs.kinetica.comwww.alachisoft.com/­resources/­docs
DeveloperDatabricksHazelcastKineticaAlachisoft
Initial release2013200820122005
Current release5.3.6, November 20237.1, August 20215.3.3, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen 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 languageJavaC, C++C#, .NET, .NET Core, Java
Server operating systemshostedAll OS with a Java VMLinuxLinux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-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.yesyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageSQL-like DML and DDL statementsSQL-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
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
Supported programming languagesPython
R
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoEvent Listeners, Executor Servicesuser defined functionsno infosupport for stored procedures with SQL-Server CLR
Triggersyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoNotifications
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated MapSource-replica replicationyes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednooptimistic locking and pessimistic locking
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.noyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlRole-based access controlAccess rights for users and roles on table levelAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)
More information provided by the system vendor
DatabricksHazelcastKineticaNCache
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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DatabricksHazelcastKineticaNCache
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