DBMS > AlaSQL vs. Databricks vs. STSdb vs. TimesTen

System Properties Comparison AlaSQL vs. Databricks vs. STSdb vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

alasql.org

www.databricks.com

github.com/STSSoft/STSdb4

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

github.com/AlaSQL/alasql

docs.databricks.com

docs.oracle.com/database/timesten-18.1

Developer

Andrey Gershun & Mathias R. Wulff

Databricks

STS Soft SC

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2013

2011

1998

Current release

4.0.8, September 2015

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

GPLv2, commercial license available

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

JavaScript

Server operating systems

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

hosted

Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

with Databricks SQL

yes

APIs and other access methods

JavaScript API

JDBC
ODBC
RESTful HTTP API

.NET Client API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

JavaScript

Python
R
Scala

C#
Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions and aggregates

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

by means of logfiles and checkpoints

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 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...
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