DBMS > CrateDB vs. InfinityDB vs. LeanXcale

System Properties Comparison CrateDB vs. InfinityDB vs. LeanXcale

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Distributed Date Store based on Lucene

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

Primary database model

Relational DBMS
Search engine

Key-value store

Key-value store
Relational DBMS

Secondary database models

Document store
Time Series DBMS

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

Score	0.97
Rank	#178	Overall
	#86	Relational DBMS
	#13	Search engines

Score	0.02
Rank	#338	Overall
	#50	Key-value stores

Score	0.18
Rank	#292	Overall
	#42	Key-value stores
	#136	Relational DBMS

Website

crate.io

boilerbay.com

www.leanxcale.com

Technical documentation

crate.io/docs

boilerbay.com/infinitydb/manual

Developer

Crate

Boiler Bay Inc.

LeanXcale

Initial release

2013

2002

2015

Current release

4.0

License

Commercial or Open Source

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

Java

Server operating systems

All OS with a Java 7 (and higher) VM

All OS with a Java VM

Data scheme

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

yes

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

yes

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.

Secondary indexes

yes

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

SQL

Support of SQL

yes, but no triggers and constraints

yes

through Apache Derby

APIs and other access methods

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
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)

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

Java

C
Java
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read Your Own Writes Consistency

for primary key lookups

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

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

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

rights management via user accounts

More information provided by the system vendor

Specific characteristics

CrateDB is an open source distributed SQL database that spreads data and processing...
» more

Full ACID and full SQL operational database with analytical queries over operational...
» more

Competitive advantages

CrateDB is typically used in operational analytics applications, particularly those...
» more

Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more

Typical application scenarios

CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
» more

Hybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more

Key customers

CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
» more

banking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more

Market metrics

The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
» more

15 beta testers
» more

Licensing and pricing models

CrateDB pricing CrateDB Community Edition is open source and free to use under the...
» more

annual fee covering license and support based on number of physical cores
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

CrateDB 4.5 takes distributed SQL database open source
24 March 2021, TechTarget

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

Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge
15 April 2021, GlobeNewswire

Crate.io extends database service offering to Google Cloud
13 April 2022, VentureBeat

CrateDB Tackles Machine Analytics with Scale-Out SQL Database
14 December 2016, Datanami

provided by Google News

Job opportunities

Database Architect
Aptos, Atlanta, GA

Data Pipeline Engineer III, Search Engineering
Mailchimp, Oakland, CA

Senior Cloud Operations Engineer
Aptos, Atlanta, GA

jobs by

Share this page