DBMS > Badger vs. JanusGraph vs. NSDb vs. Snowflake

System Properties Comparison Badger vs. JanusGraph vs. NSDb vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

github.com/dgraph-io/badger

janusgraph.org

nsdb.io

www.snowflake.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.janusgraph.org

nsdb.io/Architecture

docs.snowflake.net/manuals/index.html

Developer

DGraph Labs

Linux Foundation; originally developed as Titan by Aurelius

Snowflake Computing Inc.

Initial release

2017

2014

Current release

0.6.3, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

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

Java

Java, Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
macOS

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC
HTTP REST
WebSocket

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
Java
Python

Java
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

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

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept, user roles and pluggable authentication

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