DBMS > BigObject vs. Heroic vs. Microsoft SQL Server vs. Oracle vs. Oracle Berkeley DB

System Properties Comparison BigObject vs. Heroic vs. Microsoft SQL Server vs. Oracle vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Microsofts flagship relational DBMS

Widely used RDBMS

Widely used in-process key-value store

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

bigobject.io

github.com/spotify/heroic

www.microsoft.com/en-us/sql-server

www.oracle.com/database

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

docs.bigobject.io

spotify.github.io/heroic

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/database

docs.oracle.com/cd/E17076_05/html/index.html

Developer

BigObject, Inc.

Spotify

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2015

2014

1989

1980

1994

Current release

SQL Server 2022, November 2022

23c, September 2023

18.1.40, May 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

commercial license available

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.

Implementation language

Java

C++

C and C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

PL/SQL

also stored procedures in Java possible

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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