DBMS > RocksDB vs. Spark SQL vs. TerminusDB vs. TypeDB

System Properties Comparison RocksDB vs. Spark SQL vs. TerminusDB vs. TypeDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Spark SQL is a component on top of 'Spark Core' for structured data processing

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Key-value store

Relational DBMS

Graph DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
RDF store

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

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Score	0.81
Rank	#217	Overall
	#19	Graph DBMS
	#99	Relational DBMS

Website

Technical documentation

github.com/facebook/rocksdb/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

terminusdb.github.io/terminusdb/#

typedb.com/docs

Developer

Facebook, Inc.

Apache Software Foundation

DataChemist Ltd.

Vaticle

Initial release

2013

2014

2018

2016

Current release

8.11.4, April 2024

3.5.0 ( 2.13), September 2023

11.0.0, January 2023

2.26.3, January 2024

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

Open Source

GPL V3

Open Source

GPL Version 3, commercial licenses available

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.

Implementation language

C++

Scala

Prolog, Rust

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

C++ API
Java API

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

JavaScript
Python

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes, utilizing Spark Core

Graph Partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Journaling Streams

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Role-based access control

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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Competitive advantages

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Licensing and pricing models

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