DBMS > Dolt vs. LeanXcale vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison Dolt vs. LeanXcale vs. Microsoft Azure Table Storage vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A Wide Column Store for rapid development using massive semi-structured datasets

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Wide column store

Document store

Secondary database models

Document store

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

Score	0.60
Rank	#232	Overall
	#106	Relational DBMS

Score	0.25
Rank	#296	Overall
	#43	Key-value stores
	#133	Relational DBMS

Score	2.64
Rank	#94	Overall
	#7	Wide column stores

Score	0.20
Rank	#314	Overall
	#46	Document stores

Website

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

www.leanxcale.com

azure.microsoft.com/en-us/services/storage/tables

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

Technical documentation

docs.dolthub.com

www.xtdb.com/docs

Developer

DoltHub Inc

LeanXcale

Microsoft

Juxt Ltd.

Initial release

2018

2015

2012

2019

Current release

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

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

hosted

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

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

through Apache Derby

limited SQL, making use of Apache Calcite

APIs and other access methods

CLI Client
HTTP REST

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

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

C
Java
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Implicit feature of the cloud service

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.

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

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

User concepts

Access control

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

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

An open-source data storage and visualization platform for collaborative qubit control
30 September 2024, Nature

Top 100+ Essential Data Science Tools & Repos: Streamline Your Workflow Today!
17 October 2024, Packt

7 Modern SQL Databases You Must Know in 2024
28 June 2024, KDnuggets

Git-for-Data, Version-Controlled Database Dolt Gets PostgreSQL-Flavor
25 November 2023, infoq.com

Radar Trends to Watch: July 2022
5 July 2022, O'Reilly Media

provided by Google News

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn.com

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, HackerNoon

Inside Azure File Storage
7 October 2015, Microsoft Azure

Microsoft confirms Azure outage was human error
19 December 2014, Data Center Dynamics

provided by Google News

Share this page