DBMS > Cachelot.io vs. H2 vs. Microsoft Azure Synapse Analytics vs. PlanetScale

System Properties Comparison Cachelot.io vs. H2 vs. Microsoft Azure Synapse Analytics vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Primary database model

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Website

cachelot.io

www.h2database.com

azure.microsoft.com/services/synapse-analytics

planetscale.com

Technical documentation

www.h2database.com/html/main.html

docs.microsoft.com/azure/synapse-analytics

planetscale.com/docs

Developer

Thomas Mueller

Microsoft

PlanetScale

Initial release

2015

2005

2016

2020

Current release

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

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++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

hosted

Docker
Linux
macOS

Data scheme

schema-free

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

APIs and other access methods

Memcached protocol

JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Java

C#
Java
PHP

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Transact SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

yes

Users with fine-grained authorization concept

no user groups or roles

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