DBMS > CrateDB vs. IBM Db2 warehouse vs. Lovefield

System Properties Comparison CrateDB vs. IBM Db2 warehouse vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Cloud-based data warehousing service

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

cratedb.com

www.ibm.com/products/db2/warehouse

google.github.io/lovefield

Technical documentation

cratedb.com/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Crate

IBM

Google

Initial release

2013

2014

Current release

2.1.12, February 2017

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Java

JavaScript

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

Flexible Schema (defined schema, partial schema, 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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

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

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

.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
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript

Server-side scripts

Stored procedures

user defined functions (Javascript)

PL/SQL, SQL PL

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more

Licensing and pricing models

See CrateDB pricing >
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT
25 March 2024, PR Newswire

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions
16 May 2017, Business Wire

provided by Google News

Announcing the deprecation of prior generation Db2 Warehouse plans on AWS
16 October 2023, ibm.com

Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on ...
11 July 2023, ibm.com

Top 7 Cloud Data Warehouse Companies
31 May 2023, Datamation

The 10 Best Cloud Data Warehouse Solutions to Consider in 2024
22 October 2023, Solutions Review

Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x
11 July 2023, ibm.com

provided by Google News

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