DBMS > ArcadeDB vs. Google Cloud Datastore vs. IBM Db2 vs. Sadas Engine vs. Splunk

System Properties Comparison ArcadeDB vs. Google Cloud Datastore vs. IBM Db2 vs. Sadas Engine vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Common in IBM host environments, 2 different versions for host and Windows/Linux

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Analytics Platform for Big Data

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Search engine

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

arcadedb.com

cloud.google.com/datastore

www.ibm.com/products/db2

www.sadasengine.com

www.splunk.com

Technical documentation

docs.arcadedb.com

cloud.google.com/datastore/docs

www.ibm.com/docs/en/db2

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.splunk.com/Documentation/Splunk

Developer

Arcade Data

Google

IBM

SADAS s.r.l.

Splunk Inc.

Initial release

2021

2008

1983

host version

2006

2003

Current release

September 2021

12.1, October 2016

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free version is available

commercial

free trial version available

commercial

Limited free edition and free developer edition available

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

C and C++

C++

Server operating systems

All OS with a Java VM

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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 query language, no joins

SQL-like query language (GQL)

yes

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC
Proprietary protocol

HTTP REST

Supported programming languages

Java

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C
C#
C++
Groovy
Java
PHP
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

using Google App Engine

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using Paxos

yes

with separate tools (MQ, InfoSphere)

none

Multi-source replication

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

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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More resources

DB-Engines blog posts

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

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