DBMS > HBase vs. Interbase vs. RocksDB vs. SAP SQL Anywhere vs. TimescaleDB

System Properties Comparison HBase vs. Interbase vs. RocksDB vs. SAP SQL Anywhere vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Light-weight proven RDBMS

originally from Borland

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

hbase.apache.org

www.embarcadero.com/products/interbase

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

www.timescale.com

Technical documentation

hbase.apache.org/book.html

docs.embarcadero.com/products/interbase

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

docs.timescale.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Embarcadero

Facebook, Inc.

SAP

formerly Sybase

Timescale

Initial release

2008

1984

2013

1992

2017

Current release

2.3.4, January 2021

InterBase 2020, December 2019

8.11.4, April 2024

17, July 2015

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

BSD

commercial

Open Source

Apache 2.0

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++

Server operating systems

Linux
Unix
Windows

using Cygwin

Android
iOS
Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free, schema definition possible

yes

schema-free

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Interbase procedure and trigger language

yes, in C/C++, Java, .Net or Perl

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Interbase Change Views

yes

Source-replica replication

Database mirroring

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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