DBMS > BigObject vs. Hypertable vs. LevelDB vs. Transbase

System Properties Comparison BigObject vs. Hypertable vs. LevelDB vs. Transbase

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Analytic DBMS for real-time computations and queries

An open source BigTable implementation based on distributed file systems such as Hadoop

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Wide column store

Key-value store

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

bigobject.io

github.com/google/leveldb

www.transaction.de/en/products/transbase.html

Technical documentation

docs.bigobject.io

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

www.transaction.de/en/products/transbase/features.html

Developer

BigObject, Inc.

Hypertable Inc.

Google

Transaction Software GmbH

Initial release

2015

2009

2011

1987

Current release

0.9.8.11, March 2016

1.23, February 2021

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

GNU version 3. Commercial license available

Open Source

BSD

commercial

free development 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.

Implementation language

C++

C and C++

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
OS X
Windows

an inofficial Windows port is available

Illumos
Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

C++ API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor on file system level

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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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