DBMS > EDB Postgres vs. Riak TS vs. Spark SQL vs. XTDB

System Properties Comparison EDB Postgres vs. Riak TS vs. Spark SQL vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.enterprisedb.com

spark.apache.org/sql

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.enterprisedb.com/docs

www.tiot.jp/riak-docs/riak/ts/latest

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

www.xtdb.com/docs

Developer

EnterpriseDB

Open Source, formerly Basho Technologies

Apache Software Foundation

Juxt Ltd.

Initial release

2005

2015

2014

2019

Current release

14, December 2021

3.0.0, September 2022

3.5.0 ( 2.13), September 2023

1.19, September 2021

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

Scala

Clojure

Server operating systems

Linux
Windows

Linux
OS X

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes, limited

SQL-like DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

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

HTTP API
Native Erlang Interface

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Python
R
Scala

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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