DBMS > CrateDB vs. IBM Db2 warehouse vs. Riak TS vs. SQLite vs. Yanza

System Properties Comparison CrateDB vs. IBM Db2 warehouse vs. Riak TS vs. SQLite vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Database based on Lucene

Cloud-based data warehousing service

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Widely used embeddable, in-process RDBMS

Time Series DBMS for IoT Applications

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

cratedb.com

www.ibm.com/products/db2/warehouse

www.sqlite.org

yanza.com

Technical documentation

cratedb.com/docs

www.tiot.jp/riak-docs/riak/ts/latest

www.sqlite.org/docs.html

Developer

Crate

IBM

Open Source, formerly Basho Technologies

Dwayne Richard Hipp

Yanza

Initial release

2013

2014

2015

2000

2015

Current release

5.8.1, August 2024

3.0.0, September 2022

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

commercial

Open Source

Public Domain

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux
OS X

server-less

Windows

Data scheme

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

yes

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

restricted

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

yes, limited

yes

SQL-92 is not fully supported

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

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP API

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions (Javascript)

PL/SQL, SQL PL

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Timer and event based

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

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

via file-system locks

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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.