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DBMS > Amazon Neptune vs. Databricks vs. InfinityDB vs. Microsoft Azure Table Storage

System Properties Comparison Amazon Neptune vs. Databricks vs. InfinityDB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatabricks  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A Java embedded Key-Value Store which extends the Java Map interfaceA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Key-value storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteaws.amazon.com/­neptunewww.databricks.comboilerbay.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.databricks.comboilerbay.com/­infinitydb/­manual
DeveloperAmazonDatabricksBoiler Bay Inc.Microsoft
Initial release2017201320022012
Current release4.0
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedhostedAll OS with a Java VMhosted
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.noyesnono
Secondary indexesnoyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLnowith Databricks SQLnono
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Python
R
Scala
Java.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoImplicit feature of the cloud service
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.yesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsno infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsoptimistic 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.nonono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
Amazon NeptuneDatabricksInfinityDBMicrosoft Azure Table Storage
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon NeptuneDatabricksInfinityDBMicrosoft Azure Table Storage
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