DBMS > HBase vs. Hypertable vs. Immudb vs. Microsoft SQL Server vs. SAP SQL Anywhere

System Properties Comparison HBase vs. Hypertable vs. Immudb vs. Microsoft SQL Server vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

An open source BigTable implementation based on distributed file systems such as Hadoop

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Microsofts flagship relational DBMS

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

Primary database model

Wide column store

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

hbase.apache.org

github.com/codenotary/immudb
immudb.io

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

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

Technical documentation

hbase.apache.org/book.html

docs.immudb.io

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

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Hypertable Inc.

Codenotary

Microsoft

SAP

formerly Sybase

Initial release

2008

2009

2020

1989

1992

Current release

2.3.4, January 2021

0.9.8.11, March 2016

1.2.3, April 2022

SQL Server 2022, November 2022

17, July 2015

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
OS X
Windows

an inofficial Windows port is available

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like syntax

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

C++ API
Thrift

gRPC protocol
PostgreSQL wire protocol

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C++
Java
Perl
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

Coprocessors in Java

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

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

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor on file system level

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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