DBMS > Heroic vs. Infobright vs. Microsoft Azure Synapse Analytics vs. ObjectBox vs. Sadas Engine

System Properties Comparison Heroic vs. Infobright vs. Microsoft Azure Synapse Analytics vs. ObjectBox vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Extremely fast embedded database for small devices, IoT and Mobile

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

github.com/spotify/heroic

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/services/synapse-analytics

objectbox.io

www.sadasengine.com

Technical documentation

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

docs.objectbox.io

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Spotify

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

ObjectBox Limited

SADAS s.r.l.

Initial release

2014

2005

2016

2017

2006

Current release

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

Apache License 2.0

commercial

free trial version available

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++

C and C++

C++

Server operating systems

Linux
Windows

hosted

Android
iOS
Linux
macOS
Windows

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

Proprietary native API

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java
PHP

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

online/offline synchronization between client and server

none

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

Foreign keys

Referential integrity

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

yes

Transaction concepts

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

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.

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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