DBMS > Dolt vs. InfluxDB vs. XTDB

System Properties Comparison Dolt vs. InfluxDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

DBMS for storing time series, events and metrics

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Document store

Spatial DBMS

with GEO package

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

Score	0.60
Rank	#232	Overall
	#106	Relational DBMS

Score	21.78
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.20
Rank	#314	Overall
	#46	Document stores

Website

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

www.influxdata.com/products/influxdb-overview

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.dolthub.com

docs.influxdata.com/influxdb

www.xtdb.com/docs

Developer

DoltHub Inc

Juxt Ltd.

Initial release

2018

2013

2019

Current release

2.7.6, April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

MIT License

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

Clojure

Server operating systems

Linux
macOS
Windows

Linux
OS X

through Homebrew

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

CLI Client
HTTP REST

HTTP API
JSON over UDP

HTTP REST
JDBC

Supported programming languages

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

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Clojure
Java

Server-side scripts

Stored procedures

yes

currently in alpha release

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

in enterprise version only

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

Depending on used storage engine

User concepts

Access control

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

simple rights management via user accounts

More information provided by the system vendor

News

Hack to the Future: InfluxDB 3 Hackathon
5 May 2025

Building Smarter Manufacturing Systems with Bosch Rexroth and InfluxDB
23 April 2025

Build a Time Series Forecasting Pipeline in InfluxDB 3 Without Writing Code
17 April 2025

InfluxDB 3 Core & Enterprise GA: The Next Generation Time Series Platform for Developers is Here
15 April 2025

Deadman Alerts with the Python Processing Engine
9 April 2025

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More resources

DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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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