DBMS > Badger vs. Prometheus vs. SAP Advantage Database Server vs. VoltDB

System Properties Comparison Badger vs. Prometheus vs. SAP Advantage Database Server vs. VoltDB

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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.

Open-source Time Series DBMS and monitoring system

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

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

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

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

github.com/dgraph-io/badger

prometheus.io

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

www.voltdb.com

Technical documentation

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

prometheus.io/docs

docs.voltdb.com

Developer

DGraph Labs

Sybase, SAP

VoltDB Inc.

Initial release

2017

2015

1993

2010

Current release

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Delphi
Perl
PHP

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by Federation

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

caching of (temporary) tables can be configured

User concepts

Access control

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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