DBMS > BaseX vs. HarperDB vs. SurrealDB vs. Tarantool

System Properties Comparison BaseX vs. HarperDB vs. SurrealDB vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

A fully ACID transactional, developer-friendly, multi-model DBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Native XML DBMS

Document store

Document store
Graph DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	1.11
Rank	#174	Overall
	#30	Document stores
	#17	Graph DBMS

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Website

Technical documentation

docs.basex.org

docs.harperdb.io/docs

surrealdb.com/docs

www.tarantool.io/en/doc

Developer

BaseX GmbH

HarperDB

SurrealDB Ltd

Initial release

2007

2017

2022

2008

Current release

11.2, August 2024

3.1, August 2021

v1.5.0, May 2024

2.10.0, May 2022

License

Commercial or Open Source

Open Source

BSD license

commercial

free community edition available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

Node.js

Rust

C and C++

Server operating systems

Linux
OS X
Windows

Linux
OS X

Linux
macOS
Windows

BSD
Linux
macOS

Data scheme

schema-free

dynamic schema

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

XQuery supports types

yes

JSON data types

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

GraphQL
RESTful HTTP API
WebSocket

Open binary protocol

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.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

Deno
Go
JavaScript (Node.js)
Rust

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

Lua, C and SQL stored procedures

Triggers

yes

via events

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

the nodes on which a table resides can be defined

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

Atomic execution of specific operations

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, using LMDB

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Access rights for users and roles

yes, based on authentication and database rules

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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