DBMS > Bangdb vs. JanusGraph vs. NSDb vs. SurrealDB

System Properties Comparison Bangdb vs. JanusGraph vs. NSDb vs. SurrealDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

A Graph DBMS optimized for distributed clusters

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Graph DBMS

Time Series DBMS

Document store
Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

Technical documentation

Developer

Sachin Sinha, BangDB

Linux Foundation; originally developed as Titan by Aurelius

SurrealDB Ltd

Initial release

2012

2017

2022

Current release

BangDB 2.0, October 2021

0.6.3, February 2023

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

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, C++

Java

Java, Scala

Rust

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
macOS

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

yes: int, bigint, decimal, string

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

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC
HTTP REST
WebSocket

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java
Python

Java
Scala

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

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

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

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

Using Apache Lucene

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

User authentification and security via Rexster Graph Server

yes, based on authentication and database rules

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Database Deep Dives: JanusGraph
8 August 2019, ibm.com

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

Compose for JanusGraph arrives on Bluemix
15 September 2017, ibm.com

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

provided by Google News

SD Times Open-Source Project of the Week: SurrealDB
10 May 2024, SDTimes.com

Meet Tobie Morgan Hitchcock, CEO & Co-Founder Of SurrealDB
25 April 2024, TechRound

Cloud, privacy and AI: Trends defining the future of data and databases
27 September 2023, Sifted

SurrealDB raises $6M for its database-as-a-service offering
4 January 2023, TechCrunch

Introducing SurrealDB: A Quantum Leap in Database Technology
11 September 2023, TechRound

provided by Google News

Share this page