DBMS > DolphinDB vs. FatDB vs. SWC-DB vs. Titan vs. Yaacomo

System Properties Comparison DolphinDB vs. FatDB vs. SWC-DB vs. Titan vs. Yaacomo

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.

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Yaacomo seems to be discontinued and is removed from the DB-Engines 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 high performance, scalable Wide Column DBMS

Titan is a Graph DBMS optimized for distributed clusters.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Document store
Key-value store

Wide column store

Graph DBMS

Relational DBMS

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.dolphindb.com

github.com/kashirin-alex/swc-db
www.swcdb.org

github.com/thinkaurelius/titan

yaacomo.com

Technical documentation

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

github.com/thinkaurelius/titan/wiki

Developer

DolphinDB, Inc

FatCloud

Alex Kashirin

Aurelius, owned by DataStax

Q2WEB GmbH

Initial release

2018

2012

2020

2012

2009

Current release

v2.00.4, January 2022

0.5, April 2021

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

GPL V3

Open Source

Apache license, version 2.0

commercial

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

Server operating systems

Linux
Windows

Windows

Linux

Linux
OS X
Unix
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

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

SQL-like query language

Via inetgration in SQL Server

SQL-like query language

yes

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

Proprietary protocol
Thrift

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

Supported programming languages

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

C++

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

via pluggable storage backends

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Source-replica replication

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

yes

Transaction concepts

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

yes

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.

yes

User concepts

Access control

Administrators, Users, Groups

Can implement custom security layer via applications

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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Recent citations in the news

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17 December 2022, Ozarks Sports Zone

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Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

Beyond Titan: The Evolution of DataStax's New Graph Database
21 June 2016, Datanami

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

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14 November 2019, InfoWorld

provided by Google News

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