DBMS > Heroic vs. OrigoDB vs. SAP Advantage Database Server vs. Splunk vs. Trafodion

System Properties Comparison Heroic vs. OrigoDB vs. SAP Advantage Database Server vs. Splunk vs. Trafodion

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A fully ACID in-memory object graph database

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

Analytics Platform for Big Data

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

Search engine

Relational DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

github.com/spotify/heroic

origodb.com

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

www.splunk.com

trafodion.apache.org

Technical documentation

spotify.github.io/heroic

origodb.com/docs

docs.splunk.com/Documentation/Splunk

trafodion.apache.org/documentation.html

Developer

Spotify

Robert Friberg et al

Sybase, SAP

Splunk Inc.

Apache Software Foundation, originally developed by HP

Initial release

2014

2009

under the name LiveDB

1993

2003

2014

Current release

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Limited free edition and free developer edition available

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

Java

C++, Java

Server operating systems

Linux
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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 be achieved using .NET

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

Splunk Search Processing Language for search commands

yes

APIs and other access methods

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

.NET Client API
HTTP API
LINQ

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

.Net

Delphi
Perl
PHP

C#
Java
JavaScript
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Multi-source replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

Role based authorization

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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