DBMS > BoltDB vs. GeoMesa vs. Heroic vs. Hypertable vs. Sadas Engine

System Properties Comparison BoltDB vs. GeoMesa vs. Heroic vs. Hypertable vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An embedded key-value store for Go.

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

An open source BigTable implementation based on distributed file systems such as Hadoop

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	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

github.com/boltdb/bolt

www.geomesa.org

github.com/spotify/heroic

www.sadasengine.com

Technical documentation

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

spotify.github.io/heroic

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

Developer

CCRi and others

Spotify

Hypertable Inc.

SADAS s.r.l.

Initial release

2013

2014

2009

2006

Current release

4.0.5, February 2024

0.9.8.11, March 2016

8.0

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

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

Scala

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

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

via Elasticsearch

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

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

C++ API
Thrift

JDBC
ODBC
Proprietary protocol

Supported programming languages

C++
Java
Perl
PHP
Python
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

none

depending on storage layer

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

yes

selectable replication factor on file system level

none

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

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.

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

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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