DBMS > Google BigQuery vs. Hazelcast vs. Realm vs. Splunk vs. UniData,UniVerse

System Properties Comparison Google BigQuery vs. Hazelcast vs. Realm vs. Splunk vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A widely adopted in-memory data grid

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Analytics Platform for Big Data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

cloud.google.com/bigquery

hazelcast.com

realm.io

www.splunk.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

cloud.google.com/bigquery/docs

hazelcast.org/imdg/docs

realm.io/docs

docs.splunk.com/Documentation/Splunk

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Google

Hazelcast

Realm, acquired by MongoDB in May 2019

Splunk Inc.

Rocket Software

Initial release

2010

2008

2014

2003

1985

Current release

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

commercial

Limited free edition and free developer edition available

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

Server operating systems

hosted

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

Splunk Search Processing Language for search commands

yes

APIs and other access methods

RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

HTTP REST

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
Java
JavaScript
PHP
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Event Listeners, Executor Services

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Events

yes

Change Listeners

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

one or two-phase-commit; repeatable reads; read commited

ACID

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

ACID

configurable

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

In-Memory realm

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role-based access control

yes

Access rights for users and roles

Access rights according to SQL-standard and operating system based

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