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DBMS > Amazon Neptune vs. Apache Druid vs. LMDB vs. Quasardb vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Apache Druid vs. LMDB vs. Quasardb vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Druid  Xexclude from comparisonLMDB  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA high performant, light-weight, embedded key-value database libraryDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Key-value storeTime Series DBMSRelational 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunedruid.apache.orgwww.symas.com/­symas-embedded-database-lmdbquasar.aispark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdruid.apache.org/­docs/­latest/­designwww.lmdb.tech/­docdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software Foundation and contributorsSymasquasardbApache Software Foundation
Initial release20172012201120092014
Current release29.0.1, April 20240.9.32, January 20243.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Sourcecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++Scala
Server operating systemshostedLinux
OS X
Unix
Linux
Unix
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyes infoschema-less columns are supportedschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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 indexesnoyesnoyes infowith tagsno
SQL infoSupport of SQLnoSQL for queryingnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
RESTful HTTP/JSON API
HTTP APIJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
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
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonononono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basednoneSharding infoconsistent hashingyes, 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.yes, via HDFS, S3 or other storage enginesnoneSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient modeno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoCryptographically strong user authentication and audit trailno

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More resources
Amazon NeptuneApache DruidLMDBQuasardbSpark SQL
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