DBMS > Amazon DocumentDB vs. LeanXcale vs. XTDB vs. Yanza

System Properties Comparison Amazon DocumentDB vs. LeanXcale vs. XTDB vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Time Series DBMS for IoT Applications

Primary database model

Document store

Key-value store
Relational DBMS

Document store

Time Series DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

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

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

aws.amazon.com/documentdb

www.leanxcale.com

github.com/xtdb/xtdb
www.xtdb.com

yanza.com

Technical documentation

aws.amazon.com/documentdb/resources

www.xtdb.com/docs

Developer

LeanXcale

Juxt Ltd.

Yanza

Initial release

2019

2015

2019

2015

Current release

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Clojure

Server operating systems

hosted

All OS with a Java 8 (and higher) VM
Linux

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

through Apache Derby

limited SQL, making use of Apache Calcite

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST
JDBC

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
Java
Scala

Clojure
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes, each node contains all data

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 for users and roles

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More resources

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