DBMS > CouchDB vs. Databend vs. Google Cloud Spanner vs. Splunk vs. Stardog

System Properties Comparison CouchDB vs. Databend vs. Google Cloud Spanner vs. Splunk vs. Stardog

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Analytics Platform for Big Data

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

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

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

Website

couchdb.apache.org

github.com/datafuselabs/databend
www.databend.com

cloud.google.com/spanner

www.splunk.com

www.stardog.com

Technical documentation

docs.couchdb.org/en/stable

docs.databend.com

cloud.google.com/spanner/docs

docs.splunk.com/Documentation/Splunk

docs.stardog.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Databend Labs

Google

Splunk Inc.

Stardog-Union

Initial release

2005

2021

2017

2003

2010

Current release

3.3.3, December 2023

1.0.59, April 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

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

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

Erlang

Rust

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted
Linux
macOS

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

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

via views

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

Splunk Search Processing Language for search commands

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

APIs and other access methods

RESTful HTTP/JSON API

CLI Client
JDBC
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
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

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Go
Java
JavaScript (Node.js)
Python
Rust

Go
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

relationships in graphs

Transaction concepts

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

atomic operations within a single document possible

yes

ACID

Strict serializable isolation

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

strategy: optimistic locking

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 can be defined per database

Users with fine-grained authorization concept, user roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

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More resources

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