DBMS > BigchainDB vs. GeoMesa vs. Heroic vs. OpenTSDB vs. Sadas Engine

System Properties Comparison BigchainDB vs. GeoMesa vs. Heroic vs. OpenTSDB vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Scalable Time Series DBMS based on HBase

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

www.bigchaindb.com

www.geomesa.org

github.com/spotify/heroic

opentsdb.net

www.sadasengine.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

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

spotify.github.io/heroic

opentsdb.net/docs/build/html/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

CCRi and others

Spotify

currently maintained by Yahoo and other contributors

SADAS s.r.l.

Initial release

2016

2014

2011

2006

Current release

4.0.5, February 2024

8.0

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

LGPL

commercial

free trial version 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

Python

Scala

Java

C++

Server operating systems

Linux

Linux
Windows

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API
Telnet API

JDBC
ODBC
Proprietary protocol

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

depending on storage layer

yes

selectable replication factor

based on HBase

none

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

managed by 'Learn by Usage'

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

Exploring the 10 BEST Python Libraries for Blockchain Applications
9 September 2023, DataDrivenInvestor

Blockchain Database Startup BigchainDB Raises €3 Million
27 September 2016, CoinDesk

ascribe announces scalable blockchain database BigchainDB - CoinReport
13 February 2016, CoinReport

7 blockchain firms join Bosch led GAIA-X consortium for vehicle identity
13 September 2022, Ledger Insights

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Pinterest Switches from OpenTSDB to Their Own Time Series Database
16 September 2018, InfoQ.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

provided by Google News

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