DBMS > DataFS vs. Heroic vs. Manticore Search vs. SAP Advantage Database Server vs. Snowflake

System Properties Comparison DataFS vs. Heroic vs. Manticore Search vs. SAP Advantage Database Server vs. Snowflake

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Multi-storage database for search, including full-text search.

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Graph DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

newdatabase.com

github.com/spotify/heroic

manticoresearch.com

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

www.snowflake.com

Technical documentation

dev.mobiland.com/Overview.xsp

spotify.github.io/heroic

manual.manticoresearch.com

docs.snowflake.net/manuals/index.html

Developer

Mobiland AG

Spotify

Manticore Software

Sybase, SAP

Snowflake Computing Inc.

Initial release

2018

2014

2017

1993

2014

Current release

1.1.263, October 2022

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

yes

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

Windows

FreeBSD
Linux
macOS
Windows

Linux
Windows

hosted

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

Fixed schema

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

via Elasticsearch

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Delphi
Perl
PHP

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

no, except callback-events from server when changes happened

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

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

Windows-Profile

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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