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DBMS > Amazon DocumentDB vs. Databricks vs. NCache vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Databricks vs. NCache vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatabricks  Xexclude from comparisonNCache  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceThe 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.Open-Source and Enterprise in-memory Key-Value StoreOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument store
Relational DBMS
Key-value storeSearch engine
Secondary database modelsDocument store
Search engine infoUsing distributed Lucene
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.96
Rank#195  Overall
#29  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.databricks.comwww.alachisoft.com/­ncachesphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.databricks.comwww.alachisoft.com/­resources/­docssphinxsearch.com/­docs
DeveloperDatabricksAlachisoftSphinx Technologies Inc.
Initial release2019201320052001
Current release5.3.3, April 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEnterprise Edition availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#, .NET, .NET Core, JavaC++
Server operating systemshostedhostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counterno
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.noyesno
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnowith Databricks SQLSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.SQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Python
R
Scala
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions and aggregatesno infosupport for stored procedures with SQL-Server CLRno
Triggersnoyes infoNotificationsno
Partitioning methods infoMethods for storing different data on different nodesnoneyesSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyes, with selectable consistency levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDoptimistic locking and pessimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)no
More information provided by the system vendor
Amazon DocumentDBDatabricksNCacheSphinx
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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Amazon DocumentDBDatabricksNCacheSphinx
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