DBMS > Databricks vs. SingleStore vs. Spark SQL vs. Transbase

System Properties Comparison Databricks vs. SingleStore vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines

Name

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.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

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

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.databricks.com

www.singlestore.com

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

docs.databricks.com

docs.singlestore.com

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

Databricks

SingleStore Inc.

Apache Software Foundation

Transaction Software GmbH

Initial release

2013

2014

1987

Current release

8.5, January 2024

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

free development license

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++, Go

Scala

C and C++

Server operating systems

hosted

Linux

64 bit version required

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

but no triggers and foreign keys

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Python
R
Scala

Bash
C
C#
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

hash partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Fine grained access control via users, groups and roles

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

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

Customers in various industries worldwide including US and International Industry...
» more

Licensing and pricing models

F ree Tier and Enterprise Edition
» 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.

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More resources

DB-Engines blog posts

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9 June 2022, Akmal Chaudhri, SingleStore (sponsor)

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022, Akmal Chaudhri, SingleStore (sponsor)

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Recent citations in the news

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24 January 2024, businesswire.com

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29 January 2024, Blocks and Files

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