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DBMS > Amazon Neptune vs. Axibase vs. EXASOL vs. Google Cloud Datastore vs. Netezza

System Properties Comparison Amazon Neptune vs. Axibase vs. EXASOL vs. Google Cloud Datastore vs. Netezza

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonAxibase  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformData warehouse and analytics appliance part of IBM PureSystems
Primary database modelGraph DBMS
RDF store
Time Series DBMSRelational DBMSDocument storeRelational 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
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websiteaws.amazon.com/­neptuneaxibase.com/­docs/­atsd/­financewww.exasol.comcloud.google.com/­datastorewww.ibm.com/­products/­netezza
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.exasol.com/­resourcescloud.google.com/­datastore/­docs
DeveloperAmazonAxibase CorporationExasolGoogleIBM
Initial release20172013200020082000
Current release15585
License infoCommercial or Open Sourcecommercialcommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedLinuxhostedLinux infoincluded in appliance
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoshort, integer, long, float, double, decimal, stringyesyes, details hereyes
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.nononono
Secondary indexesnonoyesyesyes
SQL infoSupport of SQLnoSQL-like query languageyesSQL-like query language (GQL)yes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
OLE DB
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Go
Java
PHP
Python
R
Ruby
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoyesuser defined functionsusing Google App Engineyes
TriggersnoyesyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding
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 replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoHadoop integrationyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.yesno
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-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept

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More resources
Amazon NeptuneAxibaseEXASOLGoogle Cloud DatastoreNetezza infoAlso called PureData System for Analytics by IBM
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