DBMS > Coveo vs. Heroic vs. IRONdb vs. SAP Advantage Database Server vs. Tkrzw

System Properties Comparison Coveo vs. Heroic vs. IRONdb vs. SAP Advantage Database Server vs. Tkrzw

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.coveo.com

github.com/spotify/heroic

www.circonus.com/solutions/time-series-database/

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

dbmx.net/tkrzw

Technical documentation

docs.coveo.com

spotify.github.io/heroic

docs.circonus.com/irondb/category/getting-started

Developer

Coveo

Spotify

Circonus LLC.

Sybase, SAP

Mikio Hirabayashi

Initial release

2012

2014

2017

1993

2020

Current release

V0.10.20, January 2018

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

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 and C++

C++

Server operating systems

hosted

Linux

Linux
Windows

Linux
macOS

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

RESTful HTTP API

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

HTTP API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
Java
JavaScript
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Delphi
Perl
PHP

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes, in Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

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 per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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.

caching of (temporary) tables can be configured

yes

using specific database classes

User concepts

Access control

granular access controls, API key management, content filters

fine grained access rights according to SQL-standard

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