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DBMS > Amazon Neptune vs. Apache Phoenix vs. LMDB vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison Amazon Neptune vs. Apache Phoenix vs. LMDB vs. Spark SQL vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Phoenix  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA scale-out RDBMS with evolutionary schema built on Apache HBaseA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websiteaws.amazon.com/­neptunephoenix.apache.orgwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sqlvictoriametrics.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesphoenix.apache.orgwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperAmazonApache Software FoundationSymasApache Software FoundationVictoriaMetrics
Initial release20172014201120142018
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.9.32, January 20243.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCScalaGo
Server operating systemshostedLinux
Unix
Windows
Linux
Unix
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonononono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCJDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnonono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Multi-source replication
Source-replica replication
nonenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono

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Amazon NeptuneApache PhoenixLMDBSpark SQLVictoriaMetrics
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