DBMS > LeanXcale vs. Microsoft Azure Table Storage vs. OpenEdge vs. PlanetScale

System Properties Comparison LeanXcale vs. Microsoft Azure Table Storage vs. OpenEdge vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A Wide Column Store for rapid development using massive semi-structured datasets

Application development environment with integrated database management system

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

Primary database model

Key-value store
Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Website

www.leanxcale.com

azure.microsoft.com/en-us/services/storage/tables

www.progress.com/openedge

planetscale.com

Technical documentation

documentation.progress.com/output/ua/OpenEdge_latest

planetscale.com/docs

Developer

LeanXcale

Microsoft

Progress Software Corporation

PlanetScale

Initial release

2015

2012

1984

2020

Current release

OpenEdge 12.2, March 2020

License

Commercial or Open Source

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

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Docker
Linux
macOS

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

close to SQL 92

yes

with proprietary extensions

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
Java
Scala

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

Progress proprietary ABL (Advanced Business Language)

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

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

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

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

optimistic locking

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

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

Access rights based on private key authentication or shared access signatures

Users and groups

Users with fine-grained authorization concept

no user groups or roles

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