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

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

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonMemcached  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLIn-memory key-value store, originally intended for cachingScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
Relational DBMS
Key-value storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebitnine.net/­agensgraphwww.memcached.orgnsdb.iospark.apache.org/­sql
Technical documentationbitnine.net/­documentationgithub.com/­memcached/­memcached/­wikinsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBitnine Global Inc.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalApache Software Foundation
Initial release2016200320172014
Current release2.1, December 20181.6.27, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoBSD licenseOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCCJava, ScalaScala
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
OS X
Unix
Windows
Linux
macOS
Linux
OS X
Windows
Data schemedepending on used data modelschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes: int, bigint, decimal, stringyes
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 indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLyesnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsCypher Query Language
JDBC
Proprietary protocolgRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesC
Java
JavaScript
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancenoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone 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 systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesnoUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing SASL (Simple Authentication and Security Layer) protocolno

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More resources
AgensGraphMemcachedNSDbSpark SQL
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