DBMS > Datomic vs. Dolt vs. Graphite vs. Machbase Neo

System Properties Comparison Datomic vs. Dolt vs. Graphite vs. Machbase Neo

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A MySQL compatible DBMS with Git-like versioning of data and schema

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

TimeSeries DBMS for AIoT and BigData

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Website

www.datomic.com

github.com/dolthub/dolt
www.dolthub.com

github.com/graphite-project/graphite-web

machbase.com

Technical documentation

docs.datomic.com

docs.dolthub.com

graphite.readthedocs.io

machbase.com/dbms

Developer

Cognitect

DoltHub Inc

Chris Davis

Machbase

Initial release

2012

2018

2006

2013

Current release

1.0.6735, June 2023

V8.0, August 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free test version 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

Java, Clojure

Python

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Linux
Unix

Linux
macOS
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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

CLI Client
HTTP REST

HTTP API
Sockets

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

Clojure
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

currently in alpha release

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

volatile and lookup table

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

simple password-based access control

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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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