DBMS > HugeGraph vs. Prometheus vs. SAP Adaptive Server vs. SingleStore vs. SQLite

System Properties Comparison HugeGraph vs. Prometheus vs. SAP Adaptive Server vs. SingleStore vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Open-source Time Series DBMS and monitoring system

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

prometheus.io

www.sap.com/products/technology-platform/sybase-ase.html

www.singlestore.com

www.sqlite.org

Technical documentation

hugegraph.apache.org/docs

prometheus.io/docs

help.sap.com/docs/SAP_ASE

docs.singlestore.com

www.sqlite.org/docs.html

Developer

Baidu

SAP, Sybase

SingleStore Inc.

Dwayne Richard Hipp

Initial release

2018

2015

1987

2013

2000

Current release

0.9

16.0

8.5, January 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

Public Domain

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

C and C++

C++, Go

Server operating systems

Linux
macOS
Unix

Linux
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux

64 bit version required

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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.

Import of XML data possible

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

but no triggers and foreign keys

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Groovy
Java
Python

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

Bash
C
C#
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Java and Transact-SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

horizontal partitioning

Sharding

hash partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

by Federation

Multi-source replication
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Users, roles and permissions

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

More information provided by the system vendor

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Key customers

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Market metrics

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Licensing and pricing models

F ree Tier and Enterprise Edition
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