DBMS > Amazon DynamoDB vs. Apache Druid vs. JanusGraph vs. Manticore Search

System Properties Comparison Amazon DynamoDB vs. Apache Druid vs. JanusGraph vs. Manticore Search

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Graph DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

aws.amazon.com/dynamodb

druid.apache.org

janusgraph.org

manticoresearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

druid.apache.org/docs/latest/design

docs.janusgraph.org

manual.manticoresearch.com

Developer

Amazon

Apache Software Foundation and contributors

Linux Foundation; originally developed as Titan by Aurelius

Manticore Software

Initial release

2012

2017

Current release

29.0.1, April 2024

0.6.3, February 2023

6.0, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Unix

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-less columns are supported

yes

Fixed schema

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

RESTful HTTP API

JDBC
RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Clojure
Java
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

yes

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

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

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)

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

User authentification and security via Rexster Graph Server

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