DBMS > Heroic vs. InfinityDB vs. Microsoft SQL Server vs. Oracle vs. PostGIS

System Properties Comparison Heroic vs. InfinityDB vs. Microsoft SQL Server vs. Oracle vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

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

A Java embedded Key-Value Store which extends the Java Map interface

Microsofts flagship relational DBMS

Widely used RDBMS

Spatial extension of PostgreSQL

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	23.90
Rank	#29	Overall
	#1	Spatial DBMS

Website

github.com/spotify/heroic

boilerbay.com

www.microsoft.com/en-us/sql-server

www.oracle.com/database

postgis.net

Technical documentation

spotify.github.io/heroic

boilerbay.com/infinitydb/manual

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/database

postgis.net/documentation

Developer

Spotify

Boiler Bay Inc.

Microsoft

Oracle

Initial release

2014

2002

1989

1980

2005

Current release

4.0

SQL Server 2022, November 2022

23c, September 2023

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

GPL v2.0

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

Java

C++

C and C++

Server operating systems

All OS with a Java VM

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

PL/SQL

also stored procedures in Java possible

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding, horizontal partitioning

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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