DBMS > Citus vs. HarperDB vs. Oracle Rdb vs. RocksDB vs. Teradata

System Properties Comparison Citus vs. HarperDB vs. Oracle Rdb vs. RocksDB vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.citusdata.com

www.harperdb.io

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

rocksdb.org

www.teradata.com

Technical documentation

docs.citusdata.com

docs.harperdb.io/docs

www.oracle.com/database/technologies/related/rdb-doc.html

github.com/facebook/rocksdb/wiki

docs.teradata.com

Developer

HarperDB

Oracle, originally developed by Digital Equipment Corporation (DEC)

Facebook, Inc.

Teradata

Initial release

2010

2017

1984

2013

1984

Current release

8.1, December 2018

3.1, August 2021

7.4.1.1, 2021

9.2.1, May 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

free community edition available

commercial

Open Source

BSD

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

Node.js

C++

Server operating systems

Linux

Linux
OS X

HP Open VMS

Linux

hosted
Linux

Data scheme

yes

dynamic schema

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

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

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like data manipulation statements

yes

SQL 2016 + extensions

APIs and other access methods

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

C++ API
Java API

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

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Custom Functions

since release 3.1

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

horizontal partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

the nodes on which a table resides can be defined

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

yes, on a single node

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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 rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.