DBMS > Dolt vs. Vertica vs. XTDB

System Properties Comparison Dolt vs. Vertica 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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

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

Primary database model

Relational DBMS

Column oriented

Document store

Secondary database models

Document store

Spatial DBMS
Time Series DBMS

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

Score	0.60
Rank	#232	Overall
	#106	Relational DBMS

Score	9.78
Rank	#42	Overall
	#26	Relational DBMS

Score	0.20
Rank	#314	Overall
	#46	Document stores

Website

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

www.vertica.com

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

Technical documentation

docs.dolthub.com

vertica.com/documentation

www.xtdb.com/docs

Developer

DoltHub Inc

OpenText

previously Micro Focus and Hewlett Packard

Juxt Ltd.

Initial release

2018

2005

2019

Current release

12.0.3, January 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Limited community edition free

Open Source

MIT License

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Clojure

Server operating systems

Linux
macOS
Windows

Linux

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

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

limited SQL, making use of Apache Calcite

APIs and other access methods

CLI Client
HTTP REST

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

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#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Clojure
Java

Server-side scripts

Stored procedures

yes

currently in alpha release

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, hierarchical partitioning

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.

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

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

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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