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DBMS > Amazon Neptune vs. Datomic vs. LevelDB vs. NSDb vs. Solr

System Properties Comparison Amazon Neptune vs. Datomic vs. LevelDB vs. NSDb vs. Solr

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatomic  Xexclude from comparisonLevelDB  Xexclude from comparisonNSDb  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value storeTime Series DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­neptunewww.datomic.comgithub.com/­google/­leveldbnsdb.iosolr.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.datomic.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdnsdb.io/­Architecturesolr.apache.org/­resources.html
DeveloperAmazonCognitectGoogleApache Software Foundation
Initial release20172012201120172006
Current release1.0.7075, December 20231.23, February 20219.6.1, May 2024
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoBSDOpen Source infoApache Version 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Java, ScalaJava
Server operating systemshostedAll OS with a Java VMIllumos
Linux
OS X
Windows
Linux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnoyes: int, bigint, decimal, stringyes infosupports customizable data types and automatic typing
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.nonononoyes
Secondary indexesnoyesnoall fields are automatically indexedyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnononoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP APIgRPC
HTTP REST
WebSocket
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
Java
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction FunctionsnonoJava plugins
TriggersnoBy using transaction functionsnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersnoneShardingSharding
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.none infoBut extensive use of caching in the application peersnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infowith automatic compression on writesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nonoyes

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Amazon NeptuneDatomicLevelDBNSDbSolr
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