DBMS > Amazon DocumentDB vs. GeoMesa vs. JanusGraph vs. TerarkDB

System Properties Comparison Amazon DocumentDB vs. GeoMesa vs. JanusGraph vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A Graph DBMS optimized for distributed clusters

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

aws.amazon.com/documentdb

www.geomesa.org

janusgraph.org

github.com/bytedance/terarkdb

Technical documentation

aws.amazon.com/documentdb/resources

www.geomesa.org/documentation/stable/user/index.html

docs.janusgraph.org

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

CCRi and others

Linux Foundation; originally developed as Titan by Aurelius

ByteDance, originally Terark

Initial release

2019

2014

2017

2016

Current release

5.0.0, May 2024

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

restricted open source version available

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

Scala

Java

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

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

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java
Python

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

depending on storage layer

yes

none

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

Immediate Consistency

depending on storage layer

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graphs

Transaction concepts

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

Atomic single-document operations

ACID

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

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

Access rights for users and roles

yes

depending on the DBMS used for storage

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

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