DBMS > BoltDB vs. Cassandra vs. GigaSpaces vs. Hawkular Metrics

System Properties Comparison BoltDB vs. Cassandra vs. GigaSpaces vs. Hawkular Metrics

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Key-value store

Wide column store

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

Graph DBMS
Search engine

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Website

github.com/boltdb/bolt

cassandra.apache.org

www.gigaspaces.com

www.hawkular.org

Technical documentation

cassandra.apache.org/doc/latest

docs.gigaspaces.com/latest/landing.html

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Gigaspaces Technologies

Community supported by Red Hat

Initial release

2013

2008

2000

2014

Current release

4.1.3, July 2023

15.5, September 2020

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache version 2

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Java, C++, .Net

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Data scheme

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.

XML can be used for describing objects metadata

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

SQL-99 for query and DML statements

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP REST

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C++
Java
Python
Scala

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, event driven architecture

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

yes

Atomicity and isolation are supported for single operations

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 can be defined per object

Role-based access control

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

Test Drive Vector Search with DataStax Enterprise 6.9
25 June 2024

Introducing DataStax Langflow: Design and Test GenAI Apps with Ease
24 June 2024

RAGStack 1.0 Is Generally Available! A Comprehensive Solution for AI App Development
24 June 2024

An Introduction to David Jones-Gilardi, Developer Relations
11 June 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.