DBMS > Amazon Neptune vs. Apache Druid vs. BoltDB vs. Manticore Search vs. RocksDB

System Properties Comparison Amazon Neptune vs. Apache Druid vs. BoltDB vs. Manticore Search vs. RocksDB

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

An embedded key-value store for Go.

Multi-storage database for search, including full-text search.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Graph DBMS
RDF store

Relational DBMS
Time Series DBMS

Key-value store

Search engine

Key-value store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/neptune

druid.apache.org

github.com/boltdb/bolt

manticoresearch.com

rocksdb.org

Technical documentation

aws.amazon.com/neptune/developer-resources

druid.apache.org/docs/latest/design

manual.manticoresearch.com

github.com/facebook/rocksdb/wiki

Developer

Amazon

Apache Software Foundation and contributors

Manticore Software

Facebook, Inc.

Initial release

2017

2012

2013

2017

2013

Current release

29.0.1, April 2024

6.0, February 2023

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

MIT License

Open Source

GPL version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Unix

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-less columns are supported

schema-free

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL for querying

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
RESTful HTTP/JSON API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

C++ API
Java API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

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

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

The original contents of fields are not stored in the Manticore index.

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

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