DBMS > Badger vs. GeoMesa vs. Hypertable vs. SAP HANA

System Properties Comparison Badger vs. GeoMesa vs. Hypertable vs. SAP HANA

Please select another system to include it in the comparison.

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 embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

github.com/dgraph-io/badger

www.geomesa.org

www.sap.com/products/hana.html

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

help.sap.com/hana

Developer

DGraph Labs

CCRi and others

Hypertable Inc.

SAP

Initial release

2017

2014

2009

2010

Current release

5.0.0, May 2024

0.9.8.11, March 2016

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

GNU version 3. Commercial license available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Scala

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Appliance or cloud-service

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

C++ API
Thrift

JDBC
ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

selectable replication factor on file system level

yes

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

yes

depending on the DBMS used for storage

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.