DBMS > Amazon Neptune vs. Apache Druid vs. InfinityDB vs. SAP HANA

System Properties Comparison Amazon Neptune vs. Apache Druid vs. InfinityDB vs. SAP HANA

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

A Java embedded Key-Value Store which extends the Java Map interface

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Graph DBMS
RDF store

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

aws.amazon.com/neptune

druid.apache.org

boilerbay.com

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/neptune/developer-resources

druid.apache.org/docs/latest/design

boilerbay.com/infinitydb/manual

help.sap.com/hana

Developer

Amazon

Apache Software Foundation and contributors

Boiler Bay Inc.

SAP

Initial release

2017

2012

2002

2010

Current release

29.0.1, April 2024

4.0

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Linux
OS X
Unix

All OS with a Java VM

Appliance or cloud-service

Data scheme

schema-free

yes

schema-less columns are supported

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
RESTful HTTP/JSON API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-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 engines

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access 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 system

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.