DBMS > HyperSQL vs. PlanetScale vs. SAP IQ vs. WakandaDB

System Properties Comparison HyperSQL vs. PlanetScale vs. SAP IQ vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Columnar RDBMS optimized for Big Data analytics

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

column-oriented

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

hsqldb.org

planetscale.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

wakanda.github.io

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

planetscale.com/docs

help.sap.com/docs/SAP_IQ

wakanda.github.io/doc

Developer

PlanetScale

SAP, formerly Sybase

Wakanda SAS

Initial release

2001

2020

1994

2012

Current release

2.7.2, June 2023

16.1 SPS04, April 2019

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

based on BSD license

commercial

Open Source

AGPLv3, extended commercial license 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

Java

C++, JavaScript

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Docker
Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC
Java

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

Java, SQL

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

SAP/Sybase Replication Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

yes

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