DBMS > Apache Impala vs. BigchainDB vs. Heroic vs. MariaDB vs. Microsoft SQL Server

System Properties Comparison Apache Impala vs. BigchainDB vs. Heroic vs. MariaDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

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.

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

impala.apache.org

www.bigchaindb.com

github.com/spotify/heroic

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.microsoft.com/en-us/sql-server

Technical documentation

impala.apache.org/impala-docs.html

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

mariadb.com/kb/en/library

learn.microsoft.com/en-US/sql/sql-server

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Spotify

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

The lead developer Monty Widenius is the original author of MySQL

Microsoft

Initial release

2013

2016

2014

2009

Fork of MySQL, which was first released in 1995

1989

Current release

4.1.0, June 2022

11.3.2, February 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

GPL version 2, commercial enterprise subscription available

commercial

restricted free version is 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.

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SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

C++

Python

Java

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
Windows

Data scheme

yes

schema-free

yes

Dynamic columns are supported

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

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

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

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

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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