DBMS > Amazon Aurora vs. Apache Impala vs. KeyDB vs. Memgraph vs. Microsoft SQL Server

System Properties Comparison Amazon Aurora vs. Apache Impala vs. KeyDB vs. Memgraph vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Analytic DBMS for Hadoop

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

Microsofts flagship relational DBMS

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	8.50
Rank	#49	Overall
	#31	Relational DBMS

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Score	3.00
Rank	#102	Overall
	#8	Graph DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/rds/aurora

impala.apache.org

github.com/Snapchat/KeyDB
keydb.dev

memgraph.com

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

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

impala.apache.org/impala-docs.html

docs.keydb.dev

memgraph.com/docs

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

Social network pages

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

EQ Alpha Technology Ltd.

Memgraph Ltd

Microsoft

Initial release

2015

2013

2019

2017

1989

Current release

4.1.0, June 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

BSD-3

commercial

Free license available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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

hosted

Linux

Linux
Windows

Data scheme

yes

schema-free

schema-free and schema-optional

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

Bolt protocol
Cypher query language

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

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

.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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Lua

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

dynamic graph partitioning

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

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

Immediate Consistency

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

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

Optimistic locking, atomic execution of commands blocks and scripts

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

Configurable mechanisms for persistency via snapshots and/or operations logs

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

simple password-based access control and ACL

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...
» more

Licensing and pricing models

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

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