DBMS > Apache Impala vs. Hive vs. JanusGraph vs. Microsoft SQL Server vs. Splunk

System Properties Comparison Apache Impala vs. Hive vs. JanusGraph vs. Microsoft SQL Server vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Microsofts flagship relational DBMS

Analytics Platform for Big Data

Primary database model

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

impala.apache.org

hive.apache.org

janusgraph.org

www.microsoft.com/en-us/sql-server

www.splunk.com

Technical documentation

impala.apache.org/impala-docs.html

cwiki.apache.org/confluence/display/Hive/Home

docs.janusgraph.org

learn.microsoft.com/en-US/sql/sql-server

docs.splunk.com/Documentation/Splunk

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

initially developed by Facebook

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Splunk Inc.

Initial release

2013

2012

2017

1989

2003

Current release

4.1.0, June 2022

3.1.3, April 2022

0.6.3, February 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

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

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
PHP
Python

Clojure
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions and integration of map-reduce

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

yes, but depending on the SQL-Server Edition

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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, groups and roles

based on Apache Sentry and Kerberos

Access rights for users, groups and roles

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

Access rights for users and roles

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