DBMS > AnzoGraph DB vs. Spark SQL vs. Splunk vs. Trafodion

System Properties Comparison AnzoGraph DB vs. Spark SQL vs. Splunk vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Analytics Platform for Big Data

Transactional SQL-on-Hadoop DBMS

Primary database model

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

cambridgesemantics.com/anzograph

spark.apache.org/sql

www.splunk.com

trafodion.apache.org

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

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

docs.splunk.com/Documentation/Splunk

trafodion.apache.org/documentation.html

Developer

Cambridge Semantics

Apache Software Foundation

Splunk Inc.

Apache Software Foundation, originally developed by HP

Initial release

2018

2014

2003

2014

Current release

2.3, January 2021

3.5.0 ( 2.13), September 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

Apache 2.0

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

Scala

C++, Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

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

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like DML and DDL statements

Splunk Search Processing Language for search commands

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
Python

Java
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Multi-source replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

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

ACID

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

fine grained access rights according to SQL-standard

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