DBMS > atoti vs. Prometheus vs. RavenDB vs. SwayDB vs. Yaacomo

System Properties Comparison atoti vs. Prometheus vs. RavenDB vs. SwayDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Open-source Time Series DBMS and monitoring system

Open Source Operational and Transactional Enterprise NoSQL Document Database

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

yaacomo.com

Technical documentation

docs.atoti.io

prometheus.io/docs

ravendb.net/docs

Developer

ActiveViam

Hibernating Rhinos

Simer Plaha

Q2WEB GmbH

Initial release

2015

2010

2018

2009

Current release

5.4, July 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

AGPL version 3, commercial license available

Open Source

GNU Affero GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Scala

Server operating systems

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (RQL)

yes

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

Multi-source replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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