DBMS > Apache Impala vs. GeoMesa vs. MariaDB vs. Microsoft SQL Server vs. TerarkDB

System Properties Comparison Apache Impala vs. GeoMesa vs. MariaDB vs. Microsoft SQL Server vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

impala.apache.org

www.geomesa.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

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

github.com/bytedance/terarkdb

Technical documentation

impala.apache.org/impala-docs.html

www.geomesa.org/documentation/stable/user/index.html

mariadb.com/kb/en/library

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CCRi and others

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

The lead developer Monty Widenius is the original author of MySQL

Microsoft

ByteDance, originally Terark

Initial release

2013

2014

2009

Fork of MySQL, which was first released in 1995

1989

2016

Current release

4.1.0, June 2022

5.0.0, May 2024

11.3.2, February 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache License 2.0

Open Source

GPL version 2, commercial enterprise subscription available

commercial

restricted free version is available

commercial

restricted open source version 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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Implementation language

C++

Scala

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
Windows

Data scheme

yes

Dynamic columns are supported

yes

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

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

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

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

C++
Java

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

depending on storage layer

several options for horizontal partitioning and Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

depending on storage layer

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

depending on storage layer

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

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.

depending on storage layer

yes

with MEMORY storage engine

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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