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DBMS > Memcached vs. NSDb vs. Pinecone vs. Spark SQL

System Properties Comparison Memcached vs. NSDb vs. Pinecone vs. Spark SQL

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Editorial information provided by DB-Engines
NameMemcached  Xexclude from comparisonNSDb  Xexclude from comparisonPinecone  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionIn-memory key-value store, originally intended for cachingScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeTime Series DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.42
Rank#32  Overall
#4  Key-value stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.memcached.orgnsdb.iowww.pinecone.iospark.apache.org/­sql
Technical documentationgithub.com/­memcached/­memcached/­wikinsdb.io/­Architecturedocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalPinecone Systems, IncApache Software Foundation
Initial release2003201720192014
Current release1.6.27, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD licenseOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, ScalaScala
Server operating systemsFreeBSD
Linux
OS X
Unix
Windows
Linux
macOS
hostedLinux
OS X
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or datenoyes: int, bigint, decimal, stringString, Number, Booleanyes
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.nonono
Secondary indexesnoall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsProprietary protocolgRPC
HTTP REST
WebSocket
RESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Scala
PythonJava
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoRepcached, a Memcached patch, provides this functionallitynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentnoUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlyes infousing SASL (Simple Authentication and Security Layer) protocolno

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More resources
MemcachedNSDbPineconeSpark SQL
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