DBMS > Heroic vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. SQLite vs. VoltDB

System Properties Comparison Heroic vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. SQLite vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

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

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

github.com/spotify/heroic

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

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

www.voltdb.com

Technical documentation

spotify.github.io/heroic

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

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

docs.voltdb.com

Developer

Spotify

Microsoft

SAP

formerly Sybase

Dwayne Richard Hipp

VoltDB Inc.

Initial release

2014

1989

1992

2000

2010

Current release

SQL Server 2022, November 2022

17, July 2015

3.46.1 (13 August 2024), August 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Open Source

Public Domain

Open Source

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

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java, C++

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Linux
OS X

for development

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

only a subset of SQL 99

APIs and other access methods

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

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

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

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

yes, in C/C++, Java, .Net or Perl

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

none

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

Foreign keys

Referential integrity

yes

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

via file-system locks

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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