DBMS > Heroic vs. Percona Server for MongoDB vs. SAP HANA vs. Teradata

System Properties Comparison Heroic vs. Percona Server for MongoDB vs. SAP HANA vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

In-memory, column based data store. Available as appliance or cloud service

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Time Series DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
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	0.52
Rank	#254	Overall
	#39	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

github.com/spotify/heroic

www.percona.com/mongodb/software/percona-server-for-mongodb

www.sap.com/products/hana.html

www.teradata.com

Technical documentation

spotify.github.io/heroic

docs.percona.com/percona-distribution-for-mongodb

help.sap.com/hana

docs.teradata.com

Developer

Spotify

Percona

SAP

Teradata

Initial release

2014

2015

2010

1984

Current release

3.4.10-2.10, November 2017

2.0 SPS07 (April 4, 2023), April 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL Version 2

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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

Linux

Appliance or cloud-service

hosted
Linux

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

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

proprietary protocol using JSON

JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

JavaScript

SQLScript, R

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

via In-Memory Engine

yes

User concepts

Access control

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

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