DBMS > Apache Pinot vs. Google Cloud Bigtable vs. Oracle Coherence vs. SwayDB

System Properties Comparison Apache Pinot vs. Google Cloud Bigtable vs. Oracle Coherence vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Oracles in-memory data grid solution

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Key-value store
Wide column store

Key-value store

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

pinot.apache.org

cloud.google.com/bigtable

www.oracle.com/java/coherence

swaydb.simer.au

Technical documentation

docs.pinot.apache.org

cloud.google.com/bigtable/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

Apache Software Foundation and contributors

Google

Oracle

Simer Plaha

Initial release

2015

2007

2018

Current release

1.0.0, September 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GNU Affero GPL V3.0

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

Scala

Server operating systems

All OS with a Java JDK11 or higher

hosted

All OS with a Java VM

Data scheme

yes

schema-free

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.

Secondary indexes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JCache
JPA
RESTful HTTP API

Supported programming languages

Go
Java
Python

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

.Net
C++
Java

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

configurable

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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 (IAM)

authentification to access the cache via certificates or http basic authentication

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More resources

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