DBMS > CrateDB vs. Hypertable vs. Quasardb vs. SQLite

System Properties Comparison CrateDB vs. Hypertable vs. Quasardb vs. SQLite

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Distributed Database based on Lucene

An open source BigTable implementation based on distributed file systems such as Hadoop

Distributed, high-performance timeseries database

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

cratedb.com

quasar.ai

www.sqlite.org

Technical documentation

cratedb.com/docs

doc.quasar.ai/master

www.sqlite.org/docs.html

Developer

Crate

Hypertable Inc.

quasardb

Dwayne Richard Hipp

Initial release

2013

2009

2000

Current release

0.9.8.11, March 2016

3.14.1, January 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Public Domain

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.

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

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X
Windows

an inofficial Windows port is available

BSD
Linux
OS X
Windows

server-less

Data scheme

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

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

with tags

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

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

C++ API
Thrift

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

selectable replication factor on file system level

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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

via file-system locks

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

rights management via user accounts

Cryptographically strong user authentication and audit trail

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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