DBMS > atoti vs. GeoMesa vs. HarperDB vs. Prometheus

System Properties Comparison atoti vs. GeoMesa vs. HarperDB vs. Prometheus

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Editorial information provided by DB-Engines

Name

Description

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Open-source Time Series DBMS and monitoring system

Primary database model

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

Technical documentation

docs.atoti.io

www.geomesa.org/documentation/stable/user/index.html

docs.harperdb.io/docs

prometheus.io/docs

Developer

ActiveViam

CCRi and others

HarperDB

Initial release

2014

2017

2015

Current release

4.0.5, February 2024

3.1, August 2021

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache License 2.0

commercial

free community edition available

Open Source

Apache 2.0

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

Node.js

Server operating systems

Linux
OS X

Linux
Windows

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

Numeric data only

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 data manipulation statements

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

RESTful HTTP/JSON API

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Server-side scripts

Stored procedures

Python

Custom Functions

since release 3.1

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

depending on storage layer

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

the nodes on which a table resides can be defined

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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