DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Datomic vs. Postgres-XL vs. Spark SQL vs. TempoIQ

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Datomic vs. Postgres-XL vs. Spark SQL vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/analyticdb-for-mysql

www.datomic.com

www.postgres-xl.org

spark.apache.org/sql

tempoiq.com (offline)

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

docs.datomic.com

www.postgres-xl.org/documentation

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

Developer

Alibaba

Cognitect

Apache Software Foundation

TempoIQ

Initial release

2012

2014

since 2012, originally named StormDB

2014

2012

Current release

1.0.6735, June 2023

10 R1, October 2018

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Mozilla public license

Open Source

Apache 2.0

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

Java, Clojure

Scala

Server operating systems

hosted

All OS with a Java VM

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

HTTP API

Supported programming languages

C#
Java
PHP
Python

Clojure
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

Triggers

yes

By using transaction functions

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

fine grained access rights according to SQL-standard

simple authentication-based access control

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
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Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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