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DBMS > Amazon Neptune vs. Apache Druid vs. Google Cloud Spanner vs. HarperDB

System Properties Comparison Amazon Neptune vs. Apache Druid vs. Google Cloud Spanner vs. HarperDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Druid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHarperDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Relational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Websiteaws.amazon.com/­neptunedruid.apache.orgcloud.google.com/­spannerwww.harperdb.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdruid.apache.org/­docs/­latest/­designcloud.google.com/­spanner/­docsdocs.harperdb.io/­docs
DeveloperAmazonApache Software Foundation and contributorsGoogleHarperDB
Initial release2017201220172017
Current release30.0.0, June 20243.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.js
Server operating systemshostedLinux
OS X
Unix
hostedLinux
OS X
Data schemeschema-freeyes infoschema-less columns are supportedyesdynamic schema
Typing infopredefined data types such as float or dateyesyesyesyes infoJSON data types
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 indexesnoyesyesyes
SQL infoSupport of SQLnoSQL for queryingyes infoQuery statements complying to ANSI 2011SQL-like data manipulation statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresnononoCustom Functions infosince release 3.1
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedShardingA table resides as a whole on one (or more) nodes in a cluster
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.yes, via HDFS, S3 or other storage enginesMulti-source replication with 3 replicas for regional instances.yes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoStrict serializable isolationAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
Amazon NeptuneApache DruidGoogle Cloud SpannerHarperDB
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