DBMS > 4D vs. Cassandra vs. LevelDB vs. mSQL vs. TigerGraph

System Properties Comparison 4D vs. Cassandra vs. LevelDB vs. mSQL vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.4d.com

cassandra.apache.org

github.com/google/leveldb

hughestech.com.au/products/msql

www.tigergraph.com

Technical documentation

developer.4d.com

cassandra.apache.org/doc/latest

github.com/google/leveldb/blob/main/doc/index.md

docs.tigergraph.com

Developer

4D, Inc

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Hughes Technologies

Initial release

1984

2008

2011

1994

2017

Current release

v20, April 2023

4.1.3, July 2023

1.23, February 2021

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

BSD

commercial

free licenses can be provided

commercial

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Server operating systems

OS X
Windows

BSD
Linux
OS X
Windows

Illumos
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Data scheme

yes

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

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like SELECT, DML and DDL statements (CQL)

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language (GSQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC
ODBC

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

Supported programming languages

4D proprietary IDE
PHP

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Delphi
Java
Perl
PHP
Tcl

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

Representation of geographical distribution of servers is possible

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

User concepts

Access control

Users and groups

Access rights for users can be defined per object

Role-based access control

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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