DBMS > DolphinDB vs. FatDB vs. JanusGraph vs. Manticore Search

System Properties Comparison DolphinDB vs. FatDB vs. JanusGraph vs. Manticore Search

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Time Series DBMS

Document store
Key-value store

Graph DBMS

Search engine

Secondary database models

Relational DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

www.dolphindb.com

janusgraph.org

manticoresearch.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

docs.janusgraph.org

manual.manticoresearch.com

Developer

DolphinDB, Inc

FatCloud

Linux Foundation; originally developed as Titan by Aurelius

Manticore Software

Initial release

2018

2012

2017

Current release

v2.00.4, January 2022

0.6.3, February 2023

6.0, February 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++

Server operating systems

Linux
Windows

Windows

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
Windows

Data scheme

yes

schema-free

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-like query language

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Clojure
Java
Python

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

Server-side scripts

Stored procedures

yes

via applications

yes

user defined functions

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

selectable replication factor

yes

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

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.

yes

User concepts

Access control

Administrators, Users, Groups

Can implement custom security layer via applications

User authentification and security via Rexster Graph Server

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