DBMS > Databricks vs. EJDB vs. HugeGraph vs. NSDb

System Properties Comparison Databricks vs. EJDB vs. HugeGraph vs. NSDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A fast-speed and highly-scalable Graph DBMS

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

Primary database model

Document store
Relational DBMS

Document store

Graph DBMS

Time Series DBMS

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

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.databricks.com

github.com/Softmotions/ejdb

github.com/hugegraph
hugegraph.apache.org

nsdb.io

Technical documentation

docs.databricks.com

github.com/Softmotions/ejdb/blob/master/README.md

hugegraph.apache.org/docs

nsdb.io/Architecture

Developer

Databricks

Softmotions

Baidu

Initial release

2013

2012

2018

2017

Current release

0.9

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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

hosted

server-less

Linux
macOS
Unix

Linux
macOS

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

yes: int, bigint, decimal, string

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

also supports composite index and range index

all fields are automatically indexed

SQL

Support of SQL

with Databricks SQL

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

in-process shared library

Java API
RESTful HTTP API
TinkerPop Gremlin

gRPC
HTTP REST
WebSocket

Supported programming languages

Python
R
Scala

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Groovy
Java
Python

Java
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

edges in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

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

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

5. Databricks
14 May 2024, CNBC

This Is the Platform Nancy Pelosi Used to Make Her Private Investment in Databricks
9 May 2024, Yahoo Finance

AI is Driving Record Sales at Multibillion-Dollar Databricks. An IPO Can Wait … - WSJ
6 March 2024, The Wall Street Journal

Top 5 Lessons Learned from Databricks' Journey from $400M to $1.5B+
23 April 2024, SaaStr

Databricks' New Open Source LLM
8 April 2024, Forbes

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

全面升级！Apache HugeGraph 1.2.0版本发布_apach hugegraph
27 February 2024, CSDN

HugeGraph 部署和Hubble1.0.0的数据导入Bug修复_hugegraph-hubble导入数据
18 October 2023, CSDN

provided by Google News

Share this page