DBMS > Cachelot.io vs. Databricks vs. SQL.JS vs. TigerGraph vs. ToroDB

System Properties Comparison Cachelot.io vs. Databricks vs. SQL.JS vs. TigerGraph vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

In-memory caching system

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.

Port of SQLite to JavaScript

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Key-value store

Document store
Relational DBMS

Relational DBMS

Graph DBMS

Document store

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

github.com/torodb/server

Technical documentation

docs.databricks.com

sql.js.org/documentation/index.html

docs.tigergraph.com

Developer

Databricks

Alon Zakai

enhancements implemented by others

8Kdata

Initial release

2015

2013

2012

2017

2016

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

commercial

Open Source

AGPL-V3

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++

JavaScript

C++

Java

Server operating systems

FreeBSD
Linux
OS X

hosted

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

Linux

All OS with a Java 7 VM

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

yes

SQL-92 is not fully supported

SQL-like query language (GSQL)

APIs and other access methods

Memcached protocol

JDBC
ODBC
RESTful HTTP API

JavaScript API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Python
R
Scala

JavaScript

C++
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

Role-based access control

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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

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