DBMS > Amazon Redshift vs. FoundationDB vs. Spark SQL vs. Vertica vs. WakandaDB

System Properties Comparison Amazon Redshift vs. FoundationDB vs. Spark SQL vs. Vertica vs. WakandaDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Ordered key-value store. Core features are complimented by layers.

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Column oriented

Object oriented DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

aws.amazon.com/redshift

github.com/apple/foundationdb

spark.apache.org/sql

www.vertica.com

wakanda.github.io

Technical documentation

docs.aws.amazon.com/redshift

apple.github.io/foundationdb

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

vertica.com/documentation

wakanda.github.io/doc

Developer

Amazon (based on PostgreSQL)

FoundationDB

Apache Software Foundation

OpenText

previously Micro Focus and Hewlett Packard

Wakanda SAS

Initial release

2012

2013

2014

2005

2012

Current release

6.2.28, November 2020

3.5.0 ( 2.13), September 2023

12.0.3, January 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Limited community edition free

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Scala

C++

C++, JavaScript

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

yes

Typing

predefined data types such as float or date

yes

some layers support typing

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

does not fully support an SQL-standard

supported in specific SQL layer only

SQL-like DML and DDL statements

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Java
Python
R
Scala

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

in SQL-layer only

yes, PostgreSQL PL/pgSQL, with minor differences

yes

Triggers

yes, called Custom Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

horizontal partitioning, hierarchical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

in SQL-layer only

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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