DBMS > Altibase vs. Google BigQuery vs. Hypertable vs. RavenDB vs. RRDtool

System Properties Comparison Altibase vs. Google BigQuery vs. Hypertable vs. RavenDB vs. RRDtool

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

An enterprise grade, high-performance RDBMS

Large scale data warehouse service with append-only tables

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

altibase.com

cloud.google.com/bigquery

ravendb.net

oss.oetiker.ch/rrdtool

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

cloud.google.com/bigquery/docs

ravendb.net/docs

oss.oetiker.ch/rrdtool/doc

Developer

Altibase

Google

Hypertable Inc.

Hibernating Rhinos

Tobias Oetiker

Initial release

1999

2010

2009

2010

1999

Current release

v7.3, 2023, August 2023

0.9.8.11, March 2016

5.4, July 2022

1.8.0, 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

GNU version 3. Commercial license available

Open Source

AGPL version 3, commercial license available

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

AIX
HP-UX
Linux

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS
Raspberry Pi
Windows

HP-UX
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

ANSI SQL-92

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP/JSON API

C++ API
Thrift

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

in-process shared library
Pipes

Supported programming languages

C
C++
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Authorization levels configured per client per database

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