DBMS > Aerospike vs. Amazon DynamoDB vs. Faircom DB vs. Microsoft Azure Data Explorer vs. Vertica
System Properties Comparison Aerospike vs. Amazon DynamoDB vs. Faircom DB vs. Microsoft Azure Data Explorer vs. Vertica
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Aerospike previously called Citrusleaf Xexclude from comparison | Amazon DynamoDB Xexclude from comparison | Faircom DB formerly c-treeACE Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Flash-optimized In-memory NoSQL Database | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs. | Fully managed big data interactive analytics platform | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Graph DBMS leveraging Apache Tinkerpop Key-value store Spatial DBMS | Document store Key-value store | Key-value store Relational DBMS | Relational DBMS column oriented | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Spatial DBMS Time Series DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aerospike.com | aws.amazon.com/dynamodb | www.faircom.com/products/faircom-db | azure.microsoft.com/services/data-explorer | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aerospike.com | docs.aws.amazon.com/dynamodb | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | docs.microsoft.com/en-us/azure/data-explorer | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | Aerospike | Amazon | FairCom Corporation | Microsoft | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2012 | 1979 | 2019 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 7.0, November 2023 | V12, November 2020 | cloud service with continuous releases | 12.0.3, January 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache and AGPL Licenses; open sourced in June 2014; commercial Enterprise Edition available | commercial free tier for a limited amount of database operations | commercial Restricted, free version available | commercial | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | yes | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C | ANSI C, C++ | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | hosted | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | hosted | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | schema free, schema optional, schema required, partial schema, | Fixed schema with schema-less datatypes (dynamic) | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes, ANSI SQL Types, JSON, typed binary structures | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-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. | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | all fields are automatically indexed | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | no | yes, ANSI SQL with proprietary extensions | Kusto Query Language (KQL), SQL subset | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC Proprietary protocol TinkerPop Gremlin | RESTful HTTP API | ADO.NET Direct SQL JDBC JPA ODBC RESTful HTTP/JSON API RESTful MQTT/JSON API RPC | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C# C++ Erlang Go Java JavaScript (Node.js) Lua Perl PHP Python Ruby | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | .Net Go Java JavaScript (Node.js) PowerShell Python R | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions with Lua | no | yes .Net, JavaScript, C/C++ | Yes, possible languages: KQL, Python, R | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes by integration with AWS Lambda | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding Implicit feature of the cloud service | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor | yes | yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution). | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes Aerospike Aggregation Framework is similar to Map/Reduce | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency in cross-datacenter configuration and Immediate Consistency in local cluster configuration | Eventual Consistency Immediate Consistency can be specified for read operations | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Eventual Consistency Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 operations | ACID ACID across one or more tables within a single AWS account and region | tunable from ACID to Eventually Consistent | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | Yes, tunable from durable to delayed durability to in-memory | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles with Enterprise Edition only | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | Fine grained access rights according to SQL-standard with additional protections for files | Azure Active Directory Authentication | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Aerospike previously called Citrusleaf | Amazon DynamoDB | Faircom DB formerly c-treeACE | Microsoft Azure Data Explorer | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Aerospike is an enterprise-class, NoSQL database solution delivering predictable... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Optimized for use with SSDs (solid-state hard drives) Scales horizontally and vertically... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Aerospike excels in mission-critical applications that have mixed read/write workloads... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Nielsen, Williams-Sonoma, Inmobi, AppNexus, Telco (confidential), Financial Services... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Aerospike's combination of speed, scalability, and reliability delivers 10x performance... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Subscription-based Enterprise Edition and free, open-source Community Edition » more | Cost-based models and subscription-based models are both available. One license is... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Aerospike a Winner in 2024 Business Sustainability Awards New Aerospike Release Lets Enterprises Consolidate Expensive Legacy Cache And Database Platforms Aerospike Recognized by Independent Research Firm Among Notable Vendors in Vector Databases Report Aerospike Closes $109M in Growth Capital from Sumeru Equity Partners Aerospike Achieves the new AWS Advertising and Marketing Technology Competency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Aerospike previously called Citrusleaf | Amazon DynamoDB | Faircom DB formerly c-treeACE | Microsoft Azure Data Explorer | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Evaluating Hbase and Aerospike Solutions for Real-time System of Record | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Increased popularity for consuming DBMS services out of the cloud | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Aerospike a Winner in 2024 Business Sustainability Awards Aerospike raises $109M for its real-time database platform to capitalize on the AI boom Aerospike Raises $109M For Accelerated Database Development, Market Expansion Aerospike's New Release Cuts Costs by Enabling Hundreds of Caches on Small Clusters Aerospike reels in $109M to accelerate its high-speed database provided by Google News | Freecharge lowered their identity management system cost and improved scaling by switching to Amazon DynamoDB ... Migrating Uber's Ledger Data from DynamoDB to LedgerStore Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services provided by Google News | FairCom kicks off new era of database technology USA - English provided by Google News | Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services Log and Telemetry Analytics Performance Benchmark provided by Google News | Stonebraker Seeks to Invert the Computing Paradigm with DBOS How Embedded Analytics Help ISVs Overcome Challenges OpenText expands enterprise portfolio with AI and Micro Focus integrations Postgres pioneer Michael Stonebraker promises to upend the database once more OpenText integrates Micro Focus tech through Cloud Editions 23.3 provided by Google News |
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