DBMS > Heroic vs. MaxDB vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics vs. TerarkDB

System Properties Comparison Heroic vs. MaxDB vs. Microsoft Azure AI Search vs. Microsoft Azure Synapse Analytics vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

A robust and reliable RDBMS optimized to run all major SAP solutions

Search-as-a-service for web and mobile app development

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Vector DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

github.com/spotify/heroic

maxdb.sap.com

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/synapse-analytics

github.com/bytedance/terarkdb

Technical documentation

spotify.github.io/heroic

maxdb.sap.com/documentation

learn.microsoft.com/en-us/azure/search

docs.microsoft.com/azure/synapse-analytics

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Spotify

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

ByteDance, originally Terark

Initial release

2014

1984

2015

2016

Current release

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited community edition free

commercial

restricted open source 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++

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

schema-free

yes

schema-free

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

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
WebDAV

RESTful HTTP API

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

.Net
C#
Java
Perl
PHP
Python

C#
Java
JavaScript
Python

C#
Java
PHP

C++
Java

Server-side scripts

Stored procedures

yes

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Implicit feature of the cloud service

yes

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

yes

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

yes

More information provided by the system vendor

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