DBMS > HarperDB vs. Microsoft Azure Data Explorer vs. SAP Advantage Database Server vs. Sqrrl vs. Tarantool
System Properties Comparison HarperDB vs. Microsoft Azure Data Explorer vs. SAP Advantage Database Server vs. Sqrrl vs. Tarantool
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | HarperDB Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | SAP Advantage Database Server  former name: Sybase ADS Xexclude from comparison | Sqrrl Xexclude from comparison | Tarantool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking. | Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | 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. | Fully managed big data interactive analytics platform | Low-cost RDBMS with access to ISAM and FoxPro data structures | Adaptable, secure NoSQL built on Apache Accumulo | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store | Relational DBMS column oriented | Relational DBMS | Document store Graph DBMS Key-value store Wide column store | Document store Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engineTime Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Spatial DBMS with Tarantool/GIS extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.harperdb.io | azure.microsoft.com/services/data-explorer | www.sap.com/products/advantage-database-server.html | sqrrl.com | www.tarantool.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.harperdb.io/docs | docs.microsoft.com/en-us/azure/data-explorer | www.tarantool.io/en/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | HarperDB | Microsoft | Sybase, SAP | Amazon originally Sqrrl Data, Inc. | VK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2017 | 2019 | 1993 | 2012 | 2008 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 3.1, August 2021 | cloud service with continuous releases | 2.10.0, May 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free community edition available | commercial | commercial | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Node.js | Java | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X | hosted | Linux Windows | Linux | BSD Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | dynamic schema | Fixed schema with schema-less datatypes (dynamic) | yes | 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 | yes JSON data types | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | 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. | no | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | all fields are automatically indexed | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like data manipulation statements | Kusto Query Language (KQL), SQL subset | yes | no | Full-featured ANSI SQL support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC ODBC React Hooks RESTful HTTP/JSON API WebSocket | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | .NET Client API ADO.NET JDBC ODBC OLE DB | Accumulo Shell Java API JDBC ODBC RESTful HTTP API Thrift | Open binary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .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 | .Net Go Java JavaScript (Node.js) PowerShell Python R | Delphi Perl PHP | Actionscript C using GLibC# C++ Cocoa Delphi Erlang Go Haskell Java JavaScript OCaml Perl PHP Python Ruby Smalltalk | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | Custom Functions since release 3.1 | Yes, possible languages: KQL, Python, R | yes | no | Lua, C and SQL stored procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | no | yes, before/after data modification events, on replication events, client session events | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | A table resides as a whole on one (or more) nodes in a cluster | Sharding Implicit feature of the cloud service | none | Sharding making use of Hadoop | 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 | yes the nodes on which a table resides can be defined | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-source replication CONFLICT Trigger to resolve replication conflicts Source-replica replication | selectable replication factor making use of Hadoop | 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 | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution. | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replicationImmediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Atomic execution of specific operations | no | ACID | Atomic updates per row, document, or graph entity | 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 | yes | yes | yes, cooperative multitasking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes, using LMDB | yes | yes | 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 | no | no caching of (temporary) tables can be configured | yes, full featured in-memory storage engine with persistence | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users and roles | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC) | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HarperDB | Microsoft Azure Data Explorer | SAP Advantage Database Server former name: Sybase ADS | Sqrrl | Tarantool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Data processing speed and reliability: in-memory synchronous replication Startups of the Year 2023: Meet HarperDB - A Database and Application Development Platform Unlocking immersive golfing experiences with AWS Wavelength | Amazon Web Services HarperDB 4.0 Delivers Enterprise-Grade Global Application Development to Every Developer HarperDB: An underdog SQL / NoSQL database HarperDB is More Than Just a Database: Here's Why provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Azure Data Explorer and Stream Analytics for anomaly detection Controlling costs in Azure Data Explorer using down-sampling and aggregation provided by Google News SAP Announces Q3 2023 Results: Asia Pacific and Japan View AIRWORLD PART 15: WORLD'S SECOND BEST AIRPORT TERMINAL provided by Google News Amazon acquires cybersecurity startup Sqrrl Millennials possess the advantage of time for wealth creation, says Yashoraj Tyagi of Sqrrl | Mint Amazon's cloud business acquires Sqrrl, a security start-up with NSA roots AWS beefs up threat detection with Sqrrl acquisition Will Amazon Buy Cybersecurity Firm Sqrrl? provided by Google News TaranHouse: New Big Data Warehouse Announced by Tarantool In-Memory Showdown: Redis vs. Tarantool Tarantool Announces New Enterprise Version With Enhanced Scaling and Monitoring Capabilities Deploying Tarantool Cartridge applications with zero effort (Part 1) Deploying Tarantool Cartridge applications with zero effort (Part 2) provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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