DBMS > Atos Standard Common Repository vs. DolphinDB vs. InfinityDB vs. JanusGraph

System Properties Comparison Atos Standard Common Repository vs. DolphinDB vs. InfinityDB vs. JanusGraph

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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 Java embedded Key-Value Store which extends the Java Map interface

A Graph DBMS optimized for distributed clusters

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

Primary database model

Document store
Key-value store

Time Series DBMS
Vector DBMS

Key-value store

Graph DBMS

Secondary database models

Relational DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.dolphindb.com

boilerbay.com

janusgraph.org

Technical documentation

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

boilerbay.com/infinitydb/manual

docs.janusgraph.org

Developer

Atos Convergence Creators

DolphinDB, Inc

Boiler Bay Inc.

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2016

2018

2002

2017

Current release

1703

v2.00.4, January 2022

4.0

1.0.0, October 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

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

Java

C++

Java

Server operating systems

Linux

Linux
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

Schema and schema-less with LDAP views

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

optional

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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.

yes

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

LDAP

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

All languages with LDAP bindings

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

Java

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

none

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

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 or Eventual Consistency depending on configuration

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Relationships in graphs

Transaction concepts

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

Atomic execution of specific operations

yes

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

Administrators, Users, Groups

User authentification and security via Rexster Graph Server

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