DBMS > Databricks vs. Neo4j vs. ObjectBox vs. Realm vs. SQLite

System Properties Comparison Databricks vs. Neo4j vs. ObjectBox vs. Realm vs. SQLite

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.

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Extremely fast embedded database for small devices, IoT and Mobile

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Secondary database models

Time Series DBMS

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

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

www.sqlite.org/docs.html

Developer

Databricks

Neo4j, Inc.

ObjectBox Limited

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

Initial release

2013

2007

2017

2014

2000

Current release

5.20, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version3, commercial licenses available

Open Source

Apache License 2.0

Open Source

Public Domain

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java, Scala

C and C++

Server operating systems

hosted

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

Android
Backend: server-less
iOS
Windows

server-less

Data scheme

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

schema-free and schema-optional

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

with Databricks SQL

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Python
R
Scala

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net
Java

with Android only
Objective-C
React Native
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

User defined Procedures and Functions

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via event handler

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

yes using Neo4j Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Causal Clustering using Raft protocol

available in in Enterprise Version only

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

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

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

yes

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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Neo4j delivers graph technology that has been battle tested for performance and scale...
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Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
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Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.