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DBMS > Amazon Neptune vs. EXASOL vs. HEAVY.AI vs. InterSystems IRIS vs. Spark SQL

System Properties Comparison Amazon Neptune vs. EXASOL vs. HEAVY.AI vs. InterSystems IRIS vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonEXASOL  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsSpatial 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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.exasol.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.intersystems.com/­products/­intersystems-irisspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.exasol.com/­resourcesdocs.heavy.aidocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonExasolHEAVY.AI, Inc.InterSystemsApache Software Foundation
Initial release20172000201620182014
Current release5.10, January 20222023.3, June 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache 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 languageC++ and CUDAScala
Server operating systemshostedLinuxAIX
Linux
macOS
Ubuntu
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesdepending on used data modelyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononoyesno
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLnoyesyesyesSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java
Lua
Python
R
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyesno
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinShardingyes, 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 replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDno
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.yesyesyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardyesno
More information provided by the system vendor
Amazon NeptuneEXASOLHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022InterSystems IRISSpark SQL
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Amazon NeptuneEXASOLHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022InterSystems IRISSpark SQL
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