DBMS > Apache Impala vs. Cassandra vs. Datomic vs. Microsoft SQL Server vs. ToroDB

System Properties Comparison Apache Impala vs. Cassandra vs. Datomic vs. Microsoft SQL Server vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

Microsofts flagship relational DBMS

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Document store

Vector DBMS

starting with release V5

Document store
Graph DBMS
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

impala.apache.org

cassandra.apache.org

www.datomic.com

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

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

cassandra.apache.org/doc/latest

docs.datomic.com

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top level project, originally developped by Facebook

Cognitect

Microsoft

8Kdata

Initial release

2013

2008

2012

1989

2016

Current release

4.1.0, June 2022

4.1.3, July 2023

1.0.6735, June 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

limited edition free

commercial

restricted free version is available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

Java, Clojure

C++

Java

Server operating systems

Linux

BSD
Linux
OS X
Windows

All OS with a Java VM

Linux
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like SELECT, DML and DDL statements (CQL)

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

RESTful HTTP API

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

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Clojure
Java

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

Transaction Functions

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

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

But extensive use of caching in the application peers

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

none

But extensive use of caching in the application peers

yes, but depending on the SQL-Server Edition

Source-replica replication

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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Key customers

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Market metrics

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