DBMS > BigchainDB vs. Databricks vs. Heroic vs. MariaDB vs. Vertica

System Properties Comparison BigchainDB vs. Databricks vs. Heroic vs. MariaDB vs. Vertica

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

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.

Primary database model

Document store

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

www.bigchaindb.com

www.databricks.com

github.com/spotify/heroic

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.vertica.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.databricks.com

spotify.github.io/heroic

mariadb.com/kb/en/library

vertica.com/documentation

Developer

Databricks

Spotify

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2013

2014

2009

Fork of MySQL, which was first released in 1995

2005

Current release

11.3.2, February 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache 2.0

Open Source

GPL version 2, commercial enterprise subscription available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

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.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 100% GDPR-compliant.

Implementation language

Python

Java

C and C++

C++

Server operating systems

Linux

hosted

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Dynamic columns are supported

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

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

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

SQL

Support of SQL

with Databricks SQL

yes

with proprietary extensions

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

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

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

character-based, interactive, front-end utility

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Python
R
Scala

Ada
C
C#
C++
D
Eiffel
Erlang
Go
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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

PL/SQL compatibility added with version 10.3

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

Multi-source replication

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

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

not for in-memory storage engine

yes

In-memory capabilities

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

yes

with MEMORY storage engine

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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