DBMS > Amazon Redshift vs. MaxDB vs. RavenDB vs. Spark SQL vs. YottaDB

System Properties Comparison Amazon Redshift vs. MaxDB vs. RavenDB vs. Spark SQL vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A robust and reliable RDBMS optimized to run all major SAP solutions

Open Source Operational and Transactional Enterprise NoSQL Document Database

Spark SQL is a component on top of 'Spark Core' for structured data processing

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Relational DBMS

using the Octo plugin

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

maxdb.sap.com/documentation

ravendb.net/docs

spark.apache.org/docs/latest/sql-programming-guide.html

yottadb.com/resources/documentation

Developer

Amazon (based on PostgreSQL)

SAP, acquired from Software AG (Adabas-D) in 1997

Hibernating Rhinos

Apache Software Foundation

YottaDB, LLC

Initial release

2012

1984

2010

2014

2001

Current release

7.9.10.12, February 2024

5.4, July 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

AGPL version 3, commercial license available

Open Source

Apache 2.0

Open Source

AGPL 3.0

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++

Scala

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language (RQL)

SQL-like DML and DDL statements

by using the Octo plugin

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
Java
Perl
PHP
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
Python
R
Scala

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

optimistic locking

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

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

Users and groups based on OS-security mechanisms

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.