DBMS > Google Cloud Firestore vs. Splunk vs. Stardog vs. Vertica

System Properties Comparison Google Cloud Firestore vs. Splunk vs. Stardog vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Analytics Platform for Big Data

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	93.02
Rank	#13	Overall
	#2	Search engines

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

firebase.google.com/products/firestore

www.splunk.com

www.stardog.com

www.vertica.com

Technical documentation

firebase.google.com/docs/firestore

docs.splunk.com/Documentation/Splunk

docs.stardog.com

vertica.com/documentation

Developer

Google

Splunk Inc.

Stardog-Union

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2017

2003

2010

2005

Current release

7.3.0, May 2020

12.0.3, January 2023

License

Commercial or Open Source

commercial

Limited free edition and free developer edition available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Splunk Search Processing Language for search commands

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

HTTP REST

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C#
Java
JavaScript
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

user defined functions and aggregates, HTTP Server extensions in Java

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, with Cloud Functions

yes

via event handlers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication in HA-Cluster

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

yes

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, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users and roles

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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