DBMS > Databricks vs. Sequoiadb vs. Tkrzw vs. Typesense vs. Yaacomo

System Properties Comparison Databricks vs. Sequoiadb vs. Tkrzw vs. Typesense vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

NewSQL database with distributed OLTP and SQL

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Relational DBMS

Key-value store

Search engine

Relational DBMS

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

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	0.80
Rank	#209	Overall
	#14	Search engines

Website

yaacomo.com

Technical documentation

docs.databricks.com

www.sequoiadb.com/en/index.php?m=Files&a=index

typesense.org/docs

Developer

Databricks

Sequoiadb Ltd.

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2013

2020

2015

2009

Current release

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2.0

Open Source

GPL V3

commercial

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.

Implementation language

C++

Server operating systems

hosted

Linux

Linux
macOS

Linux

Android
Linux
Windows

Data scheme

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

schema-free

pre-defined schema optional

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Python
R
Scala

.Net
C++
Java
PHP
Python

C++
Java
Python
Ruby

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

user defined functions and aggregates

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Multi-source replication using RAFT

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

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

using specific database classes

yes

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» 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

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Leading Tech Talent Creation Expert Launches Databricks Data Engineer Program
19 September 2024, Business Wire

Databricks could launch IPO in two months but biding time despite investor pressure, CEO says
13 September 2024, ION Analytics

Databricks reportedly paid $2 billion in Tabular acquisition
14 August 2024, TechCrunch

Inside the Snowflake — Databricks Rivalry, and Why Both Fear Microsoft
14 August 2024, Bloomberg

Introducing Databricks AI/BI: Intelligent Analytics for Real-World Data
12 June 2024, PR Newswire

provided by Google News

Laravel Scout Adds Typesense, A Lightening-fast Open-source Search
17 January 2024, Laravel News

Building fast, fuzzy site search with Laravel and Typesense
29 July 2024, Laravel News

China win second Challenger round
10 March 2024, Scrum Queens

5 Recipe Search Engines to Cook Based on Time, Budget, & Ingredients - MUO
19 April 2022, MakeUseOf

Spain plans Six Nations alternative
13 July 2017, Scrum Queens

provided by Google News

Share this page