DBMS > Machbase vs. XTDB vs. Yaacomo

System Properties Comparison Machbase vs. XTDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Description

TimeSeries DBMS for AIoT and BigData

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Document store

Relational DBMS

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

Score	0.33
Rank	#305	Overall
	#24	Time Series DBMS

Score	0.21
Rank	#342	Overall
	#48	Document stores

Score	0.00
Rank	#389	Overall
	#160	Relational DBMS

Website

www.machbase.com

github.com/xtdb/xtdb
xtdb.com

yaacomo.com

Technical documentation

machbase.atlassian.net/wiki/spaces/MAN/overview

xtdb.com/docs

Developer

Machbase

Juxt Ltd.

Q2WEB GmbH

Initial release

2013

2019

2009

Current release

V6.5, August 2021

1.19, September 2021

License

Commercial or Open Source

commercial

free test version available

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Clojure

Server operating systems

Linux
Windows

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

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like query language

limited SQL, making use of Apache Calcite

yes

APIs and other access methods

HTTP REST
JDBC
ODBC

HTTP REST
JDBC

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Clojure
Java

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, each node contains all data

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

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