DBMS > HBase vs. InfinityDB vs. LeanXcale vs. Microsoft SQL Server vs. SAP IQ

System Properties Comparison HBase vs. InfinityDB vs. LeanXcale vs. Microsoft SQL Server vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

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

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Microsofts flagship relational DBMS

Columnar RDBMS optimized for Big Data analytics

Primary database model

Wide column store

Key-value store

Key-value store
Relational DBMS

Relational DBMS

column-oriented

Secondary database models

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	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

hbase.apache.org

boilerbay.com

www.leanxcale.com

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

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

hbase.apache.org/book.html

boilerbay.com/infinitydb/manual

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

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Boiler Bay Inc.

LeanXcale

Microsoft

SAP, formerly Sybase

Initial release

2008

2002

2015

1989

1994

Current release

2.3.4, January 2021

4.0

SQL Server 2022, November 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache version 2

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

All OS with a Java VM

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free, schema definition possible

yes

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

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

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

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

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

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java

C
Java
Scala

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

C
C#
C++
Java
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

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

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes, but depending on the SQL-Server Edition

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual 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

Single row ACID (across millions of columns)

ACID

Optimistic locking for transactions; no isolation for bulk loads

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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