DBMS > Apache Impala vs. Drizzle vs. Memgraph vs. Microsoft SQL Server vs. MonetDB

System Properties Comparison Apache Impala vs. Drizzle vs. Memgraph vs. Microsoft SQL Server vs. MonetDB

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.

Description

Analytic DBMS for Hadoop

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

An open source graph database built for real-time streaming and compatible with Neo4j

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Website

impala.apache.org

memgraph.com

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

www.monetdb.org

Technical documentation

impala.apache.org/impala-docs.html

memgraph.com/docs

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

www.monetdb.org/Documentation

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

Memgraph Ltd

Microsoft

MonetDB BV

Initial release

2013

2008

2017

1989

2004

Current release

4.1.0, June 2022

7.2.4, September 2012

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

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.

Implementation language

C++

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free and schema-optional

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

JDBC

Bolt protocol
Cypher query language

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

yes, in SQL, C, R

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

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

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

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

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

Users, roles and permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
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Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
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