DBMS > 4D vs. Databricks vs. eXtremeDB vs. TigerGraph

System Properties Comparison 4D vs. Databricks vs. eXtremeDB vs. TigerGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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.

Natively in-memory DBMS with options for persistency, high-availability and clustering

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Graph DBMS

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

Score	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

Technical documentation

developer.4d.com

docs.databricks.com

www.mcobject.com/docs/extremedb.htm

docs.tigergraph.com

Developer

4D, Inc

Databricks

McObject

Initial release

1984

2013

2001

2017

Current release

v20, April 2023

8.2, 2021

License

Commercial or Open Source

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

C and C++

C++

Server operating systems

OS X
Windows

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

with Databricks SQL

yes

with the option: eXtremeSQL

SQL-like query language (GSQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

Python
R
Scala

.Net
C
C#
C++
Java
Lua
Python
Scala

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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 (MVCC) and pessimistic (locking) strategies available

yes

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

User concepts

Access control

Users and groups

Role-based access control

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

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

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

show all

Recent citations in the news

Databricks could launch IPO in two months but biding time despite investor pressure, CEO says
13 September 2024, ION Analytics

Databricks sues patent holders over alleged 'extortion' scheme
9 September 2024, Reuters

Databricks reportedly paid $2 billion in Tabular acquisition
14 August 2024, TechCrunch

Inside the Snowflake — Databricks Rivalry, and Why Both Fear Microsoft
14 August 2024, Bloomberg

The People in Charge at Databricks as It Moves Toward a Potential IPO
24 July 2024, The Information

provided by Google News

McObject
17 November 2021, Electronic Design

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

McObject Collaborates with Wind River to Deliver First-Ever
14 September 2021, GlobeNewswire

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject and GoldenSource Collaborate on Regtech EDM Offering
28 June 2017, Financial IT

provided by Google News

TigerGraph Unveils CoPilot, Version 4.0, and New CEO
30 April 2024, Datanami

TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

How TigerGraph CoPilot enables graph-augmented AI
30 April 2024, InfoWorld

graph database Archives
26 June 2024, insideBIGDATA

TigerGraph Bolsters DB for Enterprise Graph Workloads
1 November 2023, Datanami

provided by Google News

Share this page