DBMS > Apache Ignite vs. CrateDB vs. InfinityDB

System Properties Comparison Apache Ignite vs. CrateDB vs. InfinityDB

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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.

Distributed Database based on Lucene

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

Primary database model

Key-value store
Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	2.97
Rank	#88	Overall
	#12	Key-value stores
	#47	Relational DBMS

Score	0.66
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#12	Vector DBMS

Score	0.01
Rank	#387	Overall
	#60	Key-value stores

Website

ignite.apache.org

cratedb.com

boilerbay.com

Technical documentation

apacheignite.readme.io/docs

cratedb.com/docs

boilerbay.com/infinitydb/manual

Developer

Apache Software Foundation

Crate

Boiler Bay Inc.

Initial release

2015

2013

2002

Current release

2.16.0, December 2023

5.8.1, August 2024

4.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

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 Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

All OS with a Java VM

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

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

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

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

SQL

Support of SQL

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

yes, but no triggers and constraints, and PostgreSQL compatibility

APIs and other access methods

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

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

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

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Java

Server-side scripts

Stored procedures

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

user defined functions (Javascript)

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Configurable replication on table/partition-level

none

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

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

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

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Security Hooks for custom implementations

rights management via user accounts

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More resources

Recent citations in the news

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

GridGain In-Memory Data Fabric Becomes Apache Ignite
9 April 2015, Linux.com

Apache Ignite: How to Read Data From Persistent Store
3 June 2016, dzone.com

Light a fire under Cassandra with Apache Ignite
27 April 2017, InfoWorld

provided by Google News

CrateDB Collaborates with ABB for Their industrial IoT and AI Suite
3 December 2024, PR Newswire

CrateDB Collaborates with ABB for Their industrial IoT and AI Suite
3 December 2024, WV News

CrateDB Appoints Jeff Olson as New CRO
9 July 2024, PR Newswire

Crate.io raises $10M to grow its database platform
15 June 2021, VentureBeat

Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO
1 March 2023, Business Wire

provided by Google News

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