DBMS > Hypertable vs. Ignite vs. Interbase vs. JSqlDb vs. Microsoft SQL Server

System Properties Comparison Hypertable vs. Ignite vs. Interbase vs. JSqlDb vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

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

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Light-weight proven RDBMS

originally from Borland

JavaScript Query Language Database, stores JavaScript objects and primitives

Microsofts flagship relational DBMS

Primary database model

Wide column store

Key-value store
Relational DBMS

Relational DBMS

Document store
Object oriented 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	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

ignite.apache.org

www.embarcadero.com/products/interbase

jsqldb.org (offline)

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

Technical documentation

apacheignite.readme.io/docs

docs.embarcadero.com/products/interbase

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

Developer

Hypertable Inc.

Apache Software Foundation

Embarcadero

Konrad von Backstrom

Microsoft

Initial release

2009

2015

1984

2018

1989

Current release

0.9.8.11, March 2016

Apache Ignite 2.6

InterBase 2020, December 2019

0.8, December 2018

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

commercial

Open Source

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java, .Net

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Solaris
Windows

Android
iOS
Linux
OS X
Windows

Linux
macOS
Windows

Linux
Windows

Data scheme

schema-free

yes

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

export as XML data possible

yes

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

C++ API
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

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

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

JavaScript

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

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

Interbase procedure and trigger language

functions in JavaScript

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

Triggers

yes (cache interceptors and events)

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes (replicated cache)

Interbase Change Views

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

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

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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