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DBMS > Amazon Neptune vs. GridDB vs. HEAVY.AI vs. Solr

System Properties Comparison Amazon Neptune vs. GridDB vs. HEAVY.AI vs. Solr

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable in-memory time series database optimized for IoT and Big DataA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSSpatial 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­neptunegriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
solr.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.griddb.netdocs.heavy.aisolr.apache.org/­resources.html
DeveloperAmazonToshiba CorporationHEAVY.AI, Inc.Apache Software Foundation
Initial release2017201320162006
Current release5.1, August 20225.10, January 20229.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ and CUDAJava
Server operating systemshostedLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes 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.nononoyes
Secondary indexesnoyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesSolr Parallel SQL Interface
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnononoJava plugins
Triggersnoyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinSharding
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.Source-replica replicationMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users can be defined per databasefine grained access rights according to SQL-standardyes
More information provided by the system vendor
Amazon NeptuneGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Solr
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Amazon NeptuneGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Solr
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