DBMS > IRONdb vs. Manticore Search vs. RethinkDB vs. Teradata Aster

System Properties Comparison IRONdb vs. Manticore Search vs. RethinkDB vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

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

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

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

manticoresearch.com

rethinkdb.com

Technical documentation

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

manual.manticoresearch.com

rethinkdb.com/docs

Developer

Circonus LLC.

Manticore Software

The Linux Foundation

since July 2017

Teradata

Initial release

2017

2009

2005

Current release

V0.10.20, January 2018

6.0, February 2023

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Apache Version 2

commercial

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 and C++

C++

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Linux

Data scheme

schema-free

Fixed schema

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

yes

string, binary, float, bool, date, geometry

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

in Aster File Store

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

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

SQL-like query language

yes

APIs and other access methods

HTTP API

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

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes, in Lua

user defined functions

R packages

Triggers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

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

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Synchronous replication based on Galera library

Source-replica replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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.

User concepts

Access control

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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