DBMS > Heroic vs. LevelDB vs. Oracle Berkeley DB vs. Riak TS vs. Teradata

System Properties Comparison Heroic vs. LevelDB vs. Oracle Berkeley DB vs. Riak TS vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used in-process key-value store

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

github.com/spotify/heroic

github.com/google/leveldb

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

www.teradata.com

Technical documentation

spotify.github.io/heroic

github.com/google/leveldb/blob/main/doc/index.md

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

www.tiot.jp/riak-docs/riak/ts/latest

docs.teradata.com

Developer

Spotify

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Open Source, formerly Basho Technologies

Teradata

Initial release

2014

2011

1994

2015

1984

Current release

1.23, February 2021

18.1.40, May 2020

3.0.0, September 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

commercial license available

Open Source

commercial

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

Erlang

Server operating systems

Illumos
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

hosted
Linux

Data scheme

schema-free

yes

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

yes

Secondary indexes

yes

via Elasticsearch

yes

restricted

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes, limited

yes

SQL 2016 + extensions

APIs and other access methods

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

HTTP API
Native Erlang Interface

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

Erlang

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

only for the SQL API

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

fine grained access rights according to SQL-standard

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