DBMS > Blueflood vs. Databricks vs. GeoMesa vs. LokiJS vs. Riak KV

System Properties Comparison Blueflood vs. Databricks vs. GeoMesa vs. LokiJS vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

In-memory JavaScript DBMS

Distributed, fault tolerant key-value store

Primary database model

Time Series DBMS

Document store
Relational DBMS

Spatial DBMS

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

blueflood.io

www.databricks.com

www.geomesa.org

github.com/techfort/LokiJS

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.databricks.com

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

techfort.github.io/LokiJS

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Rackspace

Databricks

CCRi and others

OpenSource, formerly Basho Technologies

Initial release

2013

2014

2009

Current release

4.0.5, February 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Scala

JavaScript

Erlang

Server operating systems

Linux
OS X

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X

Data scheme

predefined scheme

Flexible Schema (defined schema, partial schema, schema free)

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.

yes

Secondary indexes

yes

via views

restricted

SQL

Support of SQL

with Databricks SQL

APIs and other access methods

HTTP REST

JDBC
ODBC
RESTful HTTP API

JavaScript API

HTTP API
Native Erlang Interface

Supported programming languages

Python
R
Scala

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions and aggregates

View functions in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

depending on storage layer

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

depending on storage layer

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

depending on storage layer

none

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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