DBMS > Hyprcubd vs. Oracle vs. Sphinx vs. Splice Machine vs. Titan

System Properties Comparison Hyprcubd vs. Oracle vs. Sphinx vs. Splice Machine vs. Titan

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Serverless Time Series DBMS

Widely used RDBMS

Open source search engine for searching in data from different sources, e.g. relational databases

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

hyprcubd.com (offline)

www.oracle.com/database

sphinxsearch.com

splicemachine.com

github.com/thinkaurelius/titan

Technical documentation

docs.oracle.com/en/database

sphinxsearch.com/docs

splicemachine.com/how-it-works

github.com/thinkaurelius/titan/wiki

Developer

Hyprcubd, Inc.

Oracle

Sphinx Technologies Inc.

Splice Machine

Aurelius, owned by DataStax

Initial release

1980

2001

2014

2012

Current release

23c, September 2023

3.5.1, February 2023

3.1, March 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

Open Source

AGPL 3.0, commercial license available

Open Source

Apache license, version 2.0

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 and C++

C++

Java

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language (SphinxQL)

yes

APIs and other access methods

gRPC (https)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol

JDBC
Native Spark Datasource
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Shared Nothhing Auto-Sharding, Columnar Partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Yes, via Full Spark Integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

token access

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

User authentification and security via Rexster Graph Server

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