DBMS > eXtremeDB vs. Graphite vs. TypeDB

System Properties Comparison eXtremeDB vs. Graphite vs. TypeDB

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Editorial information provided by DB-Engines

Name

Description

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Graph DBMS

The type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS

The data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS

The type-theoretic data model of TypeDB subsumes the relational database model.

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

Score	0.90
Rank	#194	Overall
	#90	Relational DBMS
	#17	Time Series DBMS

Score	4.25
Rank	#63	Overall
	#4	Time Series DBMS

Score	0.59
Rank	#233	Overall
	#20	Graph DBMS
	#10	Object oriented DBMS
	#107	Relational DBMS

Website

www.mcobject.com

github.com/graphite-project/graphite-web

typedb.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

graphite.readthedocs.io

typedb.com/docs

Developer

McObject

Chris Davis

Vaticle

Initial release

2001

2006

2016

Current release

8.2, 2021

2.28.3, June 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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 and C++

Python

Java

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Unix

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

APIs and other access methods

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

HTTP API
Sockets

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)

Supported programming languages

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

JavaScript (Node.js)
Python

All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

none

Synchronous replication via raft

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

locking

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

yes

at REST API level; other APIs in progress

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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