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DBMS > Amazon Neptune vs. Apache Druid vs. HarperDB vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Apache Druid vs. HarperDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Druid  Xexclude from comparisonHarperDB  Xexclude from comparisonSplice Machine  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 dataUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Document 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
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunedruid.apache.orgwww.harperdb.iosplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdruid.apache.org/­docs/­latest/­designdocs.harperdb.io/­docssplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation and contributorsHarperDBSplice Machine
Initial release2017201220172014
Current release29.0.1, April 20243.1, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercial infofree community edition availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsJava
Server operating systemshostedLinux
OS X
Unix
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes infoschema-less columns are supporteddynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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.nonono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL for queryingSQL-like data manipulation statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
.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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoCustom Functions infosince release 3.1yes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedA table resides as a whole on one (or more) nodes in a clusterShared Nothhing Auto-Sharding, Columnar Partitioning
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 enginesyes infothe nodes on which a table resides can be definedMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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 and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneApache DruidHarperDBSplice Machine
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