DBMS > BigObject vs. BoltDB vs. Cassandra vs. HEAVY.AI vs. SiriDB

System Properties Comparison BigObject vs. BoltDB vs. Cassandra vs. HEAVY.AI vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

An embedded key-value store for Go.

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Open Source Time Series DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

bigobject.io

github.com/boltdb/bolt

cassandra.apache.org

github.com/heavyai/heavydb
www.heavy.ai

siridb.com

Technical documentation

docs.bigobject.io

cassandra.apache.org/doc/latest

docs.heavy.ai

docs.siridb.com

Developer

BigObject, Inc.

Apache Software Foundation

Apache top level project, originally developped by Facebook

HEAVY.AI, Inc.

Cesbit

Initial release

2015

2013

2008

2016

2017

Current release

4.1.3, July 2023

5.10, January 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT License

Open Source

Apache version 2

Open Source

Apache Version 2; enterprise edition available

Open Source

MIT License

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

C++ and CUDA

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

BSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like DML and DDL statements

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

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Proprietary protocol

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

JDBC
ODBC
Thrift
Vega

HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

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

Server-side scripts

Stored procedures

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Round robin

Sharding

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

yes

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Key customers

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Market metrics

Cassandra is used by 40% of the Fortune 100.
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