DBMS > ReductStore vs. SAP Adaptive Server vs. SwayDB vs. VoltDB

System Properties Comparison ReductStore vs. SAP Adaptive Server vs. SwayDB vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

github.com/reductstore
www.reduct.store

www.sap.com/products/technology-platform/sybase-ase.html

swaydb.simer.au

www.voltdb.com

Technical documentation

www.reduct.store/docs

help.sap.com/docs/SAP_ASE

docs.voltdb.com

Developer

ReductStore LLC

SAP, Sybase

Simer Plaha

VoltDB Inc.

Initial release

2023

1987

2018

2010

Current release

1.9, March 2024

16.0

11.3, April 2022

License

Commercial or Open Source

Open Source

Business Source License 1.1

commercial

Open Source

GNU Affero GPL V3.0

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

C++, Rust

C and C++

Scala

Java, C++

Server operating systems

Docker
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
OS X

for development

Data scheme

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

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
JavaScript (Node.js)
Python
Rust

C
C++
Cobol
Java
Java
Perl
PHP
Python

Java
Kotlin
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java and Transact-SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

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

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

Atomic execution of operations

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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