DBMS > atoti vs. BigObject vs. GeoMesa vs. RavenDB

System Properties Comparison atoti vs. BigObject vs. GeoMesa vs. RavenDB

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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.

Analytic DBMS for real-time computations and queries

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Object oriented DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Spatial DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

Technical documentation

docs.atoti.io

docs.bigobject.io

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

ravendb.net/docs

Developer

ActiveViam

BigObject, Inc.

CCRi and others

Hibernating Rhinos

Initial release

2015

2014

2010

Current release

4.0.5, February 2024

5.4, July 2022

License

Commercial or Open Source

commercial

free versions available

commercial

free community edition available

Open Source

Apache License 2.0

Open Source

AGPL version 3, commercial license available

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

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

Multidimensional Expressions (MDX)

SQL-like DML and DDL statements

SQL-like query language (RQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP 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

Supported programming languages

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

Server-side scripts

Stored procedures

Python

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

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.

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Read/write lock on objects (tables, trees)

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

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

Authorization levels configured per client per database

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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