DBMS > Amazon Neptune vs. Drizzle vs. Hive vs. WakandaDB vs. XTDB

System Properties Comparison Amazon Neptune vs. Drizzle vs. Hive vs. WakandaDB vs. XTDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Fast, reliable graph database built for the cloud

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

aws.amazon.com/neptune

hive.apache.org

wakanda.github.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

cwiki.apache.org/confluence/display/Hive/Home

wakanda.github.io/doc

www.xtdb.com/docs

Developer

Amazon

Drizzle project, originally started by Brian Aker

Apache Software Foundation

initially developed by Facebook

Wakanda SAS

Juxt Ltd.

Initial release

2017

2008

2012

2019

Current release

7.2.4, September 2012

3.1.3, April 2022

2.7.0 (April 29, 2019), April 2019

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache Version 2

Open Source

AGPLv3, extended commercial license available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++, JavaScript

Clojure

Server operating systems

hosted

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

with proprietary extensions

SQL-like DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC

JDBC
ODBC
Thrift

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Java
PHP

C++
Java
PHP
Python

JavaScript

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

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.

Multi-source replication
Source-replica replication

selectable replication factor

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles

yes

More information provided by the system vendor

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More resources

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