DBMS > Badger vs. GeoMesa vs. SAP Advantage Database Server vs. TimescaleDB

System Properties Comparison Badger vs. GeoMesa vs. SAP Advantage Database Server vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded 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.

Low-cost RDBMS with access to ISAM and FoxPro data structures

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

github.com/dgraph-io/badger

www.geomesa.org

www.sap.com/products/advantage-database-server.html

www.timescale.com

Technical documentation

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

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

docs.timescale.com

Developer

DGraph Labs

CCRi and others

Sybase, SAP

Timescale

Initial release

2017

2014

1993

2017

Current release

5.0.0, May 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

commercial

Open Source

Apache 2.0

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Delphi
Perl
PHP

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Source-replica replication with hot standby and reads on replicas

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

caching of (temporary) tables can be configured

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights 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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