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DBMS > Amazon Neptune vs. InfinityDB vs. IRONdb vs. Spark SQL vs. Trafodion

System Properties Comparison Amazon Neptune vs. InfinityDB vs. IRONdb vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, reliable graph database built for the cloudA Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelGraph DBMS
RDF store
Key-value storeTime Series DBMSRelational 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
Score0.00
Rank#378  Overall
#57  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptuneboilerbay.comwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqltrafodion.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperAmazonBoiler Bay Inc.Circonus LLC.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release20172002201720142014
Current release4.0V0.10.20, January 20183.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open 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 languageJavaC and C++ScalaC++, Java
Server operating systemshostedAll OS with a Java VMLinuxLinux
OS X
Windows
Linux
Data schemeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsyesyes
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 indexesnono infomanual creation possible, using inversions based on multi-value capabilitynonoyes
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonoyes, in LuanoJava Stored Procedures
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnonenoneAutomatic, metric affinity per nodeyes, utilizing Spark CoreSharding
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.noneconfigurable replication factor, datacenter awarenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsno infomanual creation possible, using inversions based on multi-value capabilitynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnonoACID
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.nononono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nononofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneInfinityDBIRONdbSpark SQLTrafodion
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