DBMS > etcd vs. jBASE vs. LeanXcale vs. Microsoft Azure Table Storage

System Properties Comparison etcd vs. jBASE vs. LeanXcale vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

A robust multi-value DBMS comprising development tools and middleware

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

Primary database model

Key-value store

Multivalue DBMS

Key-value store
Relational DBMS

Wide column store

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

etcd.io
github.com/etcd-io/etcd

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.leanxcale.com

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

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Rocket Software (formerly Zumasys)

LeanXcale

Microsoft

Initial release

1991

2015

2012

Current release

3.4, August 2019

5.7

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

FreeBSD
Linux
Windows

experimental

AIX
Linux
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

optional

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

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

yes

through Apache Derby

APIs and other access methods

gRPC
JSON over HTTP

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
Basic
Jabbascript
Java

C
Java
Scala

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

Server-side scripts

Stored procedures

yes

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

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