DBMS > Apache Impala vs. Drizzle vs. Geode vs. Microsoft SQL Server vs. ToroDB

System Properties Comparison Apache Impala vs. Drizzle vs. Geode vs. Microsoft SQL Server vs. ToroDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

Description

Analytic DBMS for Hadoop

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Microsofts flagship relational DBMS

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

Primary database model

Secondary database models

Document store

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	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

impala.apache.org

geode.apache.org

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

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

geode.apache.org/docs

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

8Kdata

Initial release

2013

2008

2002

1989

2016

Current release

4.1.0, June 2022

7.2.4, September 2012

1.1, February 2017

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

restricted free version is available

Open Source

AGPL-V3

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

C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

the JDK (8 or later) is also required

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language (OQL)

yes

APIs and other access methods

JDBC
ODBC

JDBC

Java Client API
Memcached protocol
RESTful HTTP API

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

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

user defined functions

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

Triggers

hooks for callbacks inside the server can be used.

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Multi-source replication
Source-replica replication

Multi-source replication

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights per client and object definable

fine grained access rights according to SQL-standard

Access rights for users and roles

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