DBMS > Apache Impala vs. Datomic vs. Linter vs. mSQL

System Properties Comparison Apache Impala vs. Datomic vs. Linter vs. mSQL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

RDBMS for high security requirements

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Website

impala.apache.org

www.datomic.com

linter.ru

hughestech.com.au/products/msql

Technical documentation

impala.apache.org/impala-docs.html

docs.datomic.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cognitect

relex.ru

Hughes Technologies

Initial release

2013

2012

1990

1994

Current release

4.1.0, June 2022

1.0.6735, June 2023

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Clojure

C and C++

Server operating systems

Linux

All OS with a Java VM

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Transaction Functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

Source-replica replication

none

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

Immediate Consistency

none

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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