DBMS > Amazon DynamoDB vs. Apache Impala vs. SAP SQL Anywhere vs. Spark SQL vs. Splunk

System Properties Comparison Amazon DynamoDB vs. Apache Impala vs. SAP SQL Anywhere vs. Spark SQL vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Analytic DBMS for Hadoop

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Analytics Platform for Big Data

Primary database model

Document store
Key-value store

Relational DBMS

Search engine

Secondary database models

Document store

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

aws.amazon.com/dynamodb

impala.apache.org

www.sap.com/products/technology-platform/sql-anywhere.html

spark.apache.org/sql

www.splunk.com

Technical documentation

docs.aws.amazon.com/dynamodb

impala.apache.org/impala-docs.html

help.sap.com/docs/SAP_SQL_Anywhere

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

docs.splunk.com/Documentation/Splunk

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

SAP

formerly Sybase

Apache Software Foundation

Splunk Inc.

Initial release

2012

2013

1992

2014

2003

Current release

4.1.0, June 2022

17, July 2015

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

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++

Scala

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

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

SQL-like DML and DDL statements

yes

SQL-like DML and DDL statements

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

JDBC
ODBC

HTTP REST

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in C/C++, Java, .Net or Perl

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

Database mirroring

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Access rights for users and roles

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