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DBMS > Amazon Neptune vs. Apache Impala vs. Databricks vs. Riak TS

System Properties Comparison Amazon Neptune vs. Apache Impala vs. Databricks vs. Riak TS

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for HadoopThe 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.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Relational DBMS
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websiteaws.amazon.com/­neptuneimpala.apache.orgwww.databricks.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesimpala.apache.org/­impala-docs.htmldocs.databricks.comwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksOpen Source, formerly Basho Technologies
Initial release2017201320132015
Current release4.1.0, June 20223.0.0, September 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Erlang
Server operating systemshostedLinuxhostedLinux
OS X
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesno
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.nonoyesno
Secondary indexesnoyesyesrestricted
SQL infoSupport of SQLnoSQL-like DML and DDL statementswith Databricks SQLyes, limited
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCPython
R
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesErlang
Triggersnonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
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.selectable replication factoryesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.nono
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 infobased on Apache Sentry and Kerberosno
More information provided by the system vendor
Amazon NeptuneApache ImpalaDatabricksRiak TS
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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