DBMS > Amazon Neptune vs. CrateDB vs. etcd vs. Newts vs. SAP HANA

System Properties Comparison Amazon Neptune vs. CrateDB vs. etcd vs. Newts vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Distributed Date Store based on Lucene

A distributed reliable key-value store

Time Series DBMS based on Cassandra

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

Primary database model

Graph DBMS
RDF store

Relational DBMS
Search engine

Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.09
Rank	#103	Overall
	#6	Graph DBMS
	#3	RDF stores

Score	0.94
Rank	#183	Overall
	#88	Relational DBMS
	#13	Search engines

Score	10.31
Rank	#48	Overall
	#6	Key-value stores

Score	0.00
Rank	#357	Overall
	#33	Time Series DBMS

Score	54.96
Rank	#21	Overall
	#13	Relational DBMS

Website

aws.amazon.com/neptune

crate.io

etcd.io
github.com/etcd-io/etcd

opennms.github.io/newts

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/neptune/developer-resources

crate.io/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

github.com/OpenNMS/newts/wiki

help.sap.com/hana

Developer

Amazon

Crate

OpenNMS Group

SAP

Initial release

2017

2013

2014

2010

Current release

3.4, August 2019

2.0 SPS05 (June 26, 2020), June 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

All OS with a Java 7 (and higher) VM

FreeBSD
Linux
Windows

experimental

Linux
OS X
Windows

Appliance or cloud-service

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes, but no triggers and constraints

yes

APIs and other access methods

RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin 3.3

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

gRPC
JSON over HTTP

HTTP REST
Java API

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read Your Own Writes Consistency

for primary key lookups

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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)

rights management via user accounts

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

CrateDB is typically used in operational analytics applications, particularly those...
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Typical application scenarios

CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
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Key customers

CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
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Market metrics

The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
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Licensing and pricing models

CrateDB pricing CrateDB Community Edition is open source and free to use under the...
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