DBMS > Ignite vs. InfinityDB vs. Ingres vs. Interbase vs. Snowflake

System Properties Comparison Ignite vs. InfinityDB vs. Ingres vs. Interbase vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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.

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

Well established RDBMS

Light-weight proven RDBMS

originally from Borland

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Key-value store
Relational DBMS

Key-value store

Relational DBMS

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

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

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

Score	4.67
Rank	#77	Overall
	#42	Relational DBMS

Score	5.04
Rank	#71	Overall
	#39	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

ignite.apache.org

boilerbay.com

www.actian.com/databases/ingres

www.embarcadero.com/products/interbase

www.snowflake.com

Technical documentation

apacheignite.readme.io/docs

boilerbay.com/infinitydb/manual

docs.actian.com/ingres

docs.embarcadero.com/products/interbase

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Boiler Bay Inc.

Actian Corporation

Embarcadero

Snowflake Computing Inc.

Initial release

2015

2002

1974

originally developed at University Berkely in early 1970s

1984

2014

Current release

Apache Ignite 2.6

4.0

11.2, May 2022

InterBase 2020, December 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java, .Net

Java

Server operating systems

Linux
OS X
Solaris
Windows

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Android
iOS
Linux
OS X
Windows

hosted

Data scheme

yes

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

yes

support of semi-structured data formats (JSON, XML, Avro)

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

but tools for importing/exporting data from/to XML-files available

export as XML data possible

yes

Secondary indexes

yes

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

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Java

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

yes

Interbase procedure and trigger language

user defined functions

Triggers

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

none

Ingres Replicator

Interbase Change Views

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Multiversion concurreny control

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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