DBMS > Heroic vs. IRONdb vs. Microsoft Azure Synapse Analytics vs. VoltDB

System Properties Comparison Heroic vs. IRONdb vs. Microsoft Azure Synapse Analytics vs. VoltDB

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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.

Description

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Time Series DBMS

Relational DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/spotify/heroic

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

azure.microsoft.com/services/synapse-analytics

www.voltdb.com

Technical documentation

spotify.github.io/heroic

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

docs.microsoft.com/azure/synapse-analytics

docs.voltdb.com

Developer

Spotify

Circonus LLC.

Microsoft

VoltDB Inc.

Initial release

2014

2017

2016

2010

Current release

V0.10.20, January 2018

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, C++

Server operating systems

Linux

hosted

Linux
OS X

for development

Data scheme

schema-free

yes

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

only a subset of SQL 99

APIs and other access methods

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

HTTP API

ADO.NET
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C#
Java
PHP

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

Transact SQL

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

yes

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

Eventual Consistency
Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

FOREIGN KEY constraints are not supported

Transaction concepts

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

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.

User concepts

Access control

yes

Users and roles with access to stored procedures

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